α-Synuclein (α-Syn) is a presynaptic protein primarily associated with Parkinson’s disease and other neurodegenerative diseases. The cholesterol content in SV membranes regulates α-Syn binding to synaptic vesicles, changing its function and modifying its aggregation. Using single-vesicle imaging, we show that low concentrations of cholesterol reduce vesicle clustering, and high concentrations enhance vesicle clustering mediated by α-Syn. Furthermore, using all-atom molecular dynamics simulation, we investigate the role of cholesterol in synaptic-like vesicle clustering mediated by α-Syn. In particular, we found cholesterol reduces hydrogen bonds and interaction energies in low concentrations, while high concentrations of cholesterol increase hydrogen bonds and interaction energies. Moreover, cholesterol also regulates lipid packing defects, and the condensation of cholesterol leads to the suppression of shallow packing defects, and enhancement of large defects with increasing cholesterol concentration. We revealed that cholesterol promoted vesicle clustering is due to the electrostatic interaction between cholesterol in the membrane and the N-terminal region of α-Syn. Moreover, this increased electrostatic interaction arises from a change in packing defect distribution of the protein–membrane interface induced by cholesterol condensation. This work highlights the complex interplay between α-Syn and cholesterol, emphasizing the importance of cholesterol levels in membranes and their impact on α-Syn function.

Single-molecule methods have been applied to study the mechanisms of many biophysical systems that occur on the nanometer scale. To probe the dynamics of such systems including vesicle docking, tethering, fusion, trafficking, protein-membrane interactions, etc., and to obtain reproducible experimental data; proper methodology and framework are crucial. Here, we address this need by developing a protocol for immobilization of vesicles composed of synthetic lipids and measurement using total internal reflection fluorescence (TIRF) microscopy. Furthermore, we demonstrate applications including vesicle clustering mediated by proteins such as alpha-Synuclein (αSyn) and the influence of external ions by using TIRF microscopy. Moreover, we use this method to quantify the dependence of lipid composition and charge on vesicle clustering mediated by αSyn which is based on the methods previously reported.

Mitochondrial damage, characterized by altered morphological distribution and the damage of cristae, is closely associated with mitochondrial disease. However, imaging methods for capturing mitochondrial morphology at the nanoscale level in live samples remain unavailable, which seriously hinders the accurate evaluation and diagnosis of mitochondrial-related diseases. In response, we propose a super-resolution quantification strategy based on structured illumination microscopy (SIM) for the rapid, accurate evaluation of mitochondrial morphology. Using the strategy, we accurately captured the morphological distribution of mitochondria at the nanoscale level in a way generally applicable to checking various cell processes and identifying patients with mitochondrial disease who exhibit the SLC25A46 mutation. We also used algorithm-assisted super-resolution imaging to quantitatively analyze damage to mitochondrial cristae, which supports a novel drug screening strategy—high-resolution drug screening—for investigating drugs’ pharmacodynamics on organelles in living cells. In short, our strategy improves the accurate examination of changes in mitochondrial morphology in living cells and indicates new ways in which SIM-imaging can assist in diagnosing mitochondrial disease at the single-cell level.

Technology advances in genomics, proteomics, and metabolomics largely expanded the pool of potential therapeutic targets. Compared with the in vitro setting, cell-based screening assays have been playing a key role in the processes of drug discovery and development. Besides the commonly used strategies based on colorimetric and cell viability, we reason that methods that capture the dynamic cellular events will facilitate optimal hit identification with high sensitivity and specificity. Herein, we propose a live-cell screening strategy using structured illumination microscopy (SIM) combined with an automated cell colocalization analysis software, Cellprofiler^TM, to screen and discover drugs for mitochondria and lysosomes interaction at a nanoscale resolution in living cells. This strategy quantitatively benchmarks the mitochondria-lysosome interactions such as mitochondria and lysosomes contact (MLC) and mitophagy. The automatic quantitative analysis also resolves fine changes of the mitochondria-lysosome interaction in response to genetic and pharmacological interventions. Super-resolution live-cell imaging on the basis of quantitative analysis opens up new avenues for drug screening and development by targeting dynamic organelle interactions at the nanoscale resolution, which could facilitate optimal hit identification and potentially shorten the cycle of drug discovery.