(2br) Elucidate the Role of Membrane-Bound Organelle Interactome in Parkinson’s Disease

Neurodegenerative diseases, such as Parkinson’s disease (PD) affect more than 1 million people in the United States and 6 million people worldwide. PD is an intrinsically complicated disease affecting multiple organelles, including mitochondria, lysosome, endoplasmic reticulum, synapse, and epigenetic landscape in nucleus. Onset of PD triggers dysfunction of more than one organelle mentioned above. Different cellular compartments crosstalk through direct contact or exchanging of signaling molecules. The current approaches focus on individual organelles, while neglecting the crosstalk between organelles. There is limited knowledge regarding dynamics and causal relationship between various dysfunctional organelles during the onset of PD, thus leaving the molecular mechanism of PD poorly understood. Therefore, current treatment methods for PD only alleviate symptoms rather than cure. To fill this knowledge gap, the goal of my future research group is to systematically quantify organelle interaction of neurons during PD progression and build organelle interaction network that drives PD onset. To do that, we will 1) establish a humanized brain culture model consisting of different neuron types; 2) build a library of toolset to probe and perturb protein-protein interaction (PPI) across various organelles; and 3) explore the organelle interactome via advanced quantitative microscopy coupled with machine learning algorithm to predict causal relationship from timelapse dataset. The foundation of my proposed research is built upon my research expertise in cell biology, protein engineering and system biology. I have proved the feasibility of my future research directions by successfully deriving dopaminergic (DA) neurons from human induced pluripotent stem cells (hiPSCs). PD-like phenotype was observed in hiPSC-derived DA neurons exposed to atrazine at developmental stage. Furthermore, my previous work with live-cell compatible probe targeting mitochondrial DNA methylation. In this work, we developed toolset to track methylation level of mitochondrial DNA and nuclear DNA simultaneously and observed an unsynchronized dynamic during cell cycle. Additionally, I performed quantitative measurement of interaction of two heterochromatin markers, namely ^meCpG and H3K9me3, using fluorescent lifetime imaging microscope (FLIM), during neuron differentiation. In another project, I used regression-based model to predict dominant epigenetic features that can distinguish cells from different treatment group. Collectively, my training from PhD research will support my accomplishment of proposed research goals. I expect that the research framework can be further extended to other neurodegenerative disease, such as Alzheimer’s Disease and Huntington’s Disease. Furthermore, I will also seek to help with K12 education with my research project, specifically female students aiming to do STEM major during their college education. Women neuroscientists and chemical engineers are, unfortunately, still under-represented in academics. I expect by offering more research opportunity in my lab to female K12 students, participation of female students in STEM research will be encouraged.

Teaching Interests

I am interested in teaching various types of undergraduate level ChE courses, including but not limited to Thermodynamics, Transport Phenomena and Reaction Kinetics. I am also willing to develop graduate level electives with specific focus on using engineering approach to understand disease onset in neuroscience. During my PhD career, I did 2 teaching assistant jobs, one with graduate-level transport phenomena class and another one with undergraduate level lab. I am also fortunate to guest-lectured undergraduate Thermodynamic class. Therefore, I have gained experience in teaching during my PhD years and am confident to accomplish my teaching goal during my future faculty career.