Graduation Year

2025

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Medicine

Major Professor

Gopal Thinakaran, Ph.D.

Committee Member

Stanley Stevens Jr., Ph.D.

Committee Member

Lianchun Wang, Ph.D.

Committee Member

Bradlee Heckmann, Ph.D.

Committee Member

Rex Philpot, Ph.D.

Keywords

Bridging integrator 1, N2a cells, Neurons, Protein-protein interaction, TurboID

Abstract

The gene BIN1 is the second-largest genetic risk factor for late-onset Alzheimer’s disease (LOAD). It is expressed in neurons and glia in the brain as cell-type specific and ubiquitous isoforms. BIN1 is an adaptor protein that regulates membrane dynamics in many cell types. Previously, we reported that BIN1 predominantly localizes to presynaptic terminals in neurons and regulates presynaptic vesicular release. However, the function of neuronal BIN1 in relation to LOAD is not yet fully understood. A significant gap in the field is the unbiased characterization of neuronal BIN1-interacting proteins and proximal neighbors. To address this gap and help define the functions of neuronal BIN1 in the brain, we employed TurboID-based proximity labeling to identify proteins biotinylated by the neuronal BIN1 isoform 1-TurboID fusion protein (BIN1iso1-TID) in cultured mouse neuroblastoma (N2a) cells in vitro and in adult mouse brain neurons in vivo. Label-free quantification-based proteomic analysis of the BIN1iso1-TID biotinylated proteins led to the discovery of 360 proteins in N2a cells and 897 proteins in mouse brain neurons, identified as BIN1iso1-associated (proximal) or interacting proteins. A total of 92 proteins were common in both datasets, indicating that these are high-confidence BIN1-interacting or proximity proteins. SynapticGO analysis of the mouse brain dataset revealed that BIN1iso1-TurboID labeled 159 synaptic proteins, with 60 corresponding to the synaptic vesicle cycle. Based on phosphorylation site analysis of the neuronal BIN1iso1-TID interactome and related kinase prediction, we selected AAK1, CDK16, SYNJ1, PP2BA, and RANG for validation through immunostaining and proximity ligation assays as members of the BIN1 interactome in the mouse brain. We extended these studies to Alzheimer’s disease utilizing the same approach of BIN1iso1-TID proximity labeling in 5XFAD mice with the goal of determining how amyloid pathology affects the BIN1 interactome. To investigate this, we compared the BIN1iso1 interactomes of 5XFAD mice at an early time point before high amyloid burden compared to older animals where amyloid pathology is documented to cause synaptic dysfunction. Through this approach, we discovered 1034 proteins in young 5XFAD mice and 1085 protein hits in old 5XFAD mice. These datasets corresponded well with the homeostatic neuronal BIN1 interactome, sharing 541 proteins between them and replicating many of the top hits from homeostatic neurons. The young and old 5XFAD BIN1 interactomes were compared and analyzed with GO and network analyses, revealing enrichment in amyloid-associated pathways of oxidative stress, autophagy, and apoptosis, providing novel targets for investigating BIN1-associated LOAD-risk. Analysis of contrasting proteins between the groups allowed us to prioritize potential interactors such as BLNK and PPIF for further validation. These datasets provide a foundational framework for future hypothesis-driven studies that will elucidate BIN1’s amyloid-specific functions to better understand BIN1’s role in LOAD.

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Neurosciences Commons

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