Synaptic dysfunction is a common feature of neuropsychiatric disease. For example, a hallmark of age-related neurodegenerative diseases such as Alzheimer?s and Parkinson?s is synaptic fibrilization and aggregation of key proteins that participate in synapse and cell loss. Maladaptive plastic changes in synapse structure and function underlie key aspects of behavioral and mood disorders ranging from addiction to depression, as well as neurodevelopmental diseases like schizophrenia and autism. It is for these reasons that many investigators across a range of neuroscience disciplines study the synapse, and the reason that new tools to study synapse structure and function within neural circuits of interest are sorely needed. Indeed, current tools to assess synapse structure in defined cell types are not readily compatible with state-of-the-art 3D volume approaches such as serial block face scanning electron microscopy, and are severely hampered by inadequate computational tools for quantitative assessment of these massive datasets. However, advances in molecular genetics, optics, engineering and computing provide new opportunities to develop information rich strategies to peer into the synapse. Here, we combine such advances to achieve a new state-of-the-art in imaging and analyzing microcircuit connectivity and synapse structure within neurotransmitter-defined neural networks. Specifically, we leverage the fact that the bulk of signaling across the synapse is mediated by a relatively small population of small molecule neurotransmitters that are synthesized and packaged into synaptic vesicles at the site of release in axonal compartments. The bulk of neurotransmission is thus dependent on just seven well- described vesicular transporters expressed in brain. Our overall goal is to build a rigorous, easily deployable, cell-type-specific, expandable, multi-functional toolkit for imaging and quantifying neurotransmitter-defined synaptic connections by both light and electron microscopy in mice. To accomplish this, we will use CRISPR/Cas9 to insert electron microscopy-compatible tags into native vesicular transporters (Aim 1), establish simplified procedures for their monochrome and ?multicolor? labeling in 3D ultrastructure (Aim 2), and computational tools for automated segmentation and quantitative analysis of key pre- and post-synaptic metrics (Aim 3). Though these Aims are independently meritorious, by synthesizing them we aim to generate a complete toolkit that will allow investigators to render neurotransmitter-defined circuit connections into 3D ultrastructure datasets with automated quantitative assessment of key features of pre- and post-synaptic structure.

Public Health Relevance

Synaptic and structural dysfunction are causally related to both the causes and symptoms of neuropsychiatric illness ranging from Alzheimer?s disease to addiction and depression. Modern advances in molecular genetics, engineering, materials, and computer sciences have created new opportunities to understand how brain dysfunction gives rise to disease. Here, we leverage these interdisciplinary advances to develop new probes, new methods, and new analysis pipelines to study the normal and pathological structure and function of synaptically coupled brain cells.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
1RF1MH120685-01
Application #
9822844
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Alvarez, Ruben P
Project Start
2019-08-01
Project End
2022-07-31
Budget Start
2019-08-01
Budget End
2022-07-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Neurosciences
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093