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Choi, M. L.

Publications and source records attributed to Choi, M. L..

4 recordsLinked to original sources

Protein aggregation and calcium dysregulation are the earliest hallmarks of synucleinopathy in human midbrain dopaminergic neurons

Mutations in the SNCA gene cause autosomal dominant Parkinsons disease (PD), with progressive loss of dopaminergic neurons in the substantia nigra, and accumulation of aggregates of -synuclein. However, the sequence of molecular events that proceed from the SNCA mutation during development, to its end stage pathology is unknown. Utilising human induced pluripotent stem cells (hiPSCs) with SNCA mutations, we resolved the temporal sequence of pathophysiological events that occur during neuronal differentiation in order to discover the early, and likely causative, events in synucleinopathies. We adapted a small molecule-based protocol that generates highly enriched midbrain dopaminergic (mDA) neurons (>80%). We characterised their molecular identity using single-cell RNA sequencing and their functional identity through the synthesis and secretion of dopamine, the ability to generate action potentials, and form functional synapses and networks. RNA velocity analyses confirmed the developmental transcriptomic trajectory of midbrain neural precursors into mDA neurons using our approach, and identified key driver genes in mDA neuronal development. To characterise the synucleinopathy, we adopted super-resolution methods to determine the number, size and structure of aggregates in SNCA-mutant mDA neurons. At one week of differentiation, prior to maturation to mDA neurons of molecular and functional identity, we demonstrate the formation of small aggregates; specifically, {beta}-sheet rich oligomeric aggregates, in SNCA-mutant midbrain immature neurons. The aggregation progresses over time to accumulate phosphorylated aggregates, and later fibrillar aggregates. When the midbrain neurons were functional, we observed evidence of impaired physiological calcium signalling, with raised basal calcium, and impairments in cytosolic and mitochondrial calcium efflux. Once midbrain identity fully developed, SNCA-mutant neurons exhibited bioenergetic impairments, mitochondrial dysfunction and oxidative stress. During the maturation of mDA neurons, upregulation of mitophagy and autophagy occured, and ultimately these multiple cellular stresses lead to an increase in cell death by six weeks post-differentiation. Our differentiation paradigm generates an efficient model for studying disease mechanisms in PD, and highlights that protein misfolding to generate intraneuronal oligomers is one of the earliest critical events driving disease in human neurons, rather than a late-stage hallmark of the disease.

neuroscience↗

Structural conversion of α-synuclein at the mitochondria induces neuronal toxicity

Aggregation of -Synuclein (-Syn) drives Parkinsons disease, although the initial stages of self-assembly and structural conversion have not been captured inside neurons. We track the intracellular conformational states of -Syn utilizing a single-molecule FRET biosensor, and show that -Syn converts from its monomeric state to form two distinct oligomeric states in neurons in a concentration dependent, and sequence specific manner. 3D FRET-CLEM reveals the structural organization, and location of aggregation hotspots inside the cell. Notably multiple intracellular seeding events occur preferentially on membrane surfaces, especially mitochondrial membranes. The mitochondrial lipid, cardiolipin triggers rapid oligomerization of A53T -Syn, and cardiolipin is sequestered within aggregating lipid-protein complexes. Mitochondrial aggregates impair complex I activity and increase mitochondrial ROS generation, which accelerates the oligomerization of A53T -Syn, and ultimately causes permeabilization of mitochondrial membranes, and cell death. Patient iPSC derived neurons harboring A53T mutations exhibit accelerated oligomerization that is dependent on mitochondrial ROS, early mitochondrial permeabilization and neuronal death. Our study highlights a mechanism of de novo oligomerization at the mitochondria and its induction of neuronal toxicity.

neuroscience↗

Deep learning in human neurons predicts mechanistic subtypes of Parkinson's

Parkinsons disease (PD) is a common, devastating, and incurable neurodegenerative disorder. Several molecular mechanisms have been proposed to drive PD, with genetic and pathological evidence pointing towards aberrant protein homeostasis and mitochondrial dysfunction. PD is clinically highly heterogeneous, it is likely that different mechanisms underlie the pathology in different individuals, each requiring a specific targeted treatment. Recent advances in stem cell technology and fluorescent live-cell imaging have enabled the generation of patient-derived neurons with different mechanistic subtypes of PD. Here, we performed multi-dimensional fluorescent labelling of organelles in iPSC-derived neurons, in healthy control cells, and in four different disease subclasses. We generated a machine learning-based model that can simultaneously predict the presence of disease, and its primary mechanistic subtype. We independently trained a series of classifiers using both quantitative single-cell fluorescence variables and images to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whilst image based deep neural networks predict control, and four distinct disease subtypes with an accuracy of 95%. The classifiers achieve their accuracy across all subtypes primarily utilizing the organellar features of the mitochondria, with additional contribution of the lysosomes, confirming their biological importance in PD. Taken together, we show that machine learning approaches applied to patient-derived cells are able to predict disease subtypes, demonstrating that this approach may be used to guide personalized treatment approaches in the future.

cell biology↗

Highly enriched hiPSC-derived midbrain dopaminergic neurons robustly models Parkinson's disease.

The development of human induced pluripotent stem cells (hiPSC) has greatly aided our ability to model neurodegenerative diseases. However, generation of midbrain dopaminergic (mDA) neurons is a major challenge and protocols are variable. Here, we developed a method to differentiate hiPSCs into enriched populations (>80%) of mDA neurons using only small molecules. We confirmed the identity of the mDA neurons using single-cell RNA-sequencing and detection of classical markers. Single-cell live imaging demonstrated neuronal calcium signalling and functional dopamine transport. Electrophysiology measures highlighted the ability to form synapses and networks in culture. Patient-specific hiPSC lines differentiated to produce functional mDA neurons that exhibit the hallmarks of synucleinopathy including: aggregate formation, oxidative stress as well as mitochondrial dysfunction and impaired lysosomal dynamics. In summary, we establish a robust differentiation paradigm to generate enriched mDA neurons from hiPSCs, which can be used to faithfully model key aspects of Parkinsons disease (PD), providing the potential to further elucidate molecular mechanisms contributing to disease development.

neuroscience↗