| NSF Org: |
DBI Division of Biological Infrastructure |
| Recipient: |
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| Initial Amendment Date: | July 31, 2017 |
| Latest Amendment Date: | July 14, 2019 |
| Award Number: | 1707401 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Edda Thiels
ethiels@nsf.gov (703)292-8167 DBI Division of Biological Infrastructure BIO Directorate for Biological Sciences |
| Start Date: | September 1, 2017 |
| End Date: | August 31, 2021 (Estimated) |
| Total Intended Award Amount: | $2,097,912.00 |
| Total Awarded Amount to Date: | $2,097,912.00 |
| Funds Obligated to Date: |
FY 2018 = $674,185.00 FY 2019 = $684,450.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
615 W 131ST ST NEW YORK NY US 10027-7922 (212)854-6851 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1212 Amsterdam Ave; Fairchilld New York NY US 10027-7922 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Cross-BIO Activities |
| Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.074 |
ABSTRACT
The human brain is composed of billions of interconnected neurons that form highly complex neuronal circuits that process information and encode behavior. Many questions about these interconnected networks are unanswered: How variable are they from individual to individual, how do they change throughout life, how does the environment impact on them, and what are the genetic blueprints that generate these networks. Disruptions of the genetic blueprints that build neuronal networks are the likely cause of many human neurological diseases. In order to study neuronal networks in the brain, it is of paramount interest to easily visualize the patterns of connectivity of neurons, ideally in the context of live organisms. The cellular complexity of brains prevents such types of studies in complex organisms, and this project therefore uses a simple invertebrate model system, the nematode C.elegans, to visualize all the major neuronal connections of its simple nervous system. Previous studies have amply demonstrated that mechanisms of brain patterning discovered in C.elegans are conserved in other animals as well. The investigators develop and use cutting-edge fluorescent reporter technology, combined with microscopical and computer vision technology to achieve this goal. The project's construction of animals in which most neuronal connections are fluorescently labeled provides a major resource. This resource is made available to the large field of C.elegans researchers who with that resource can study the many questions that relate to circuits in the brain, including the decoding of the nervous system's genetic blueprint. In addition, the project includes cutting-edge, interdisciplinary training opportunities for undergraduate and graduate students from diverse backgrounds, as well as postdoctoral fellows.
The project entails the development and dissemination of tools that empower the C.elegans neuroscience community to study the connectome of the nematode C.elegans. In the first phase, the technology hub develops two sets of tools: One group uses fluorescent-based reporter technology (GRASP and iBlinc as potential alternative) to generate a large number of transgenic C.elegans strains in which the main "edges" of the entire wiring diagram (i.e., pairwise combinations of neurons) are visualized. As part of this project, this resource is distributed throughout the C.elegans community to enable labs with long-standing interest in various aspects of neuronal development and function and with a focus on specific neuronal circuits and behaviors to use these synaptic labels to examine variability, development, and plasticity of these connections. In parallel, the other group develops microfluidic-based and automated image analysis technologies to precisely quantify the structure of the connectome and to enable high-throughput screening of worm population for defects in synaptic wiring. Computer vision and machine learning is used to score automatically disruptions of synaptic wiring to detect subtle changes in wiring. This NeuroTechnology Hub award is part of the BRAIN Initiative and NSF's Understanding the Brain activities.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Visualizing synaptic connectivity in the brain has traditionally relied on electron microscopy-based imaging approaches, which are exceptionally time- and resource-consuming. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established that employ transgenic animals approaches. These range from the labeling of specific components of chemical or electrical synapses, to split reporter gene technology (GRASP, iBlinc). During this funding period, we – a collabaroting team of two laboratories located at Georgia Tech and Atlanta and Columbia University in New York - have developed WormPsyQi, an image analysis pipeline that semi-automatically scores synaptically localized fluorescent signals in a high-throughput manner. We provide proof-of-concept studies in the approach using the simple animal model system C. elegans. We generated a resource of 40 transgenic strains that label electrical or chemical synapses throughout the nervous system of the nematode C. elegans, using either presynaptic markers, transsynaptic GRASP markers or electrical synapse proteins. We show that WormPsyQi performs well on them despite variance in neuron morphologies, synaptic signals, and image parameters. This growing synapse labeling toolkit represents a powerful resource for further analysis of synaptic structure in C. elegans and paves the way for similar recordings in more complex animals. We use our toolkit to establish a number of parameters of synaptic structure, ranging from developmental growth to inter-individual variability.
Last Modified: 10/23/2021
Modified by: Oliver Hobert
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