As the molecular components of organelles are understood in greater detail, there is a growing need for quantitative approaches to determine how changes in protein expression in cells affect organelle composition and function. The larger goal of this work is to develop sensitive single- molecule and nanofluidic techniques that allow quantification of organelle composition with increasing sensitivity and apply them to understanding synaptic vesicle recycling. In the last funding cycle, we developed a quantitative TIRF (total-internal-reflection fluorescence) microscopy technique to quantify the major membrane proteins of synaptic vesicles isolated from brain. A key feature of this approach is that it uses the entire distribution of calibration data, not just the average. A major finding of our work was that vesicle proteins fall into two classes, those that are generally monodispersed (vary little in protein number between vesicles) and those that are polydispersed (vary considerably between vesicles). This suggests that changes in the expression levels of monodispersed proteins are more likely to lead to pathological changes in vesicle functioning than changes in the expression of polydispersed proteins. The goal of the current proposal is to test this hypothesis. To do so we propose four aims: 1) Develop a high-throughput quantification system that utilizes a flow-through technique based on optical gradient flow focusing and single-molecule detection, 2) Develop an analytical scale vesicle purification process to enable analysis of synaptic vesicles from genetically manipulated neurons, 3) Test the effects of protein over expression on vesicle protein contents, and 4) Develop and utilize a quantitative fluorescence microscopy approach for quantification of protein number and variability at the level of the synapse. Completion of the above aims will result in both a new level of understanding of synaptic vesicle assembly and new powerful tools for manipulating and quantitating a wide range of sub-cellular organelles, protein complexes, and other biological nanoparticles.
Changes in synaptic vesicle protein expression are associated with both normal processes like learning and memory and with a number of pathologies ranging from schizophrenia to epilepsy. The goal of this work is to develop sensitive single-molecule and nanofluidic techniques that allow quantification of organelle composition with increasing sensitivity and apply them to understanding synaptic vesicle recycling. Gaining a better understanding of synaptic composition and function may provide the basis for the development of novel therapies for CNS dysfunction that act by modulating synaptic function;additionally, the tools we develop should find broad use in the analysis of other subcellular organelles.
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