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oai:dspace.mit.edu:1721.1/1513782023-08-01T03:43:27Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024

Boyden, Edward S. Shim, Seung Hyeon Massachusetts Institute of Technology. Department of Biological Engineering 2023-07-31T19:35:19Z 2023-07-31T19:35:19Z 2023-06 2023-05-31T22:49:58.485Z https://hdl.handle.net/1721.1/151378 https://orcid.org/0009-0007-1072-6883 Mapping the connectivity of neurons, or the brain connectome, with a clear identification of neuron types and functions is a complicated problem that hinders the development of potential therapeutic interventions. Without understanding the identities of neurons that have fundamental roles in neurological or psychiatric disorders, uncovering the disease mechanism and pathology to observe, control, and even repair neural dynamics remains challenging. In this work, we achieve live animal imaging and cell identification by generating a multicolored fluorescent map of different neurons in C. elegans. We take advantage of neuron type-specific promoters to construct transgenes that label each neuron type with unique red, green, and blue fluorescent colors. We also tag subcellular markers of the nucleolus and nuclear membrane with fluorescent proteins to allow for a combinatorial barcode for neuron types, allowing the differentiation of neurons at a single-cell resolution. Through multicolor barcoding of individual neurons, we distinguish different cell types in vivo, helping reconstruct parts of the C. elegans connectome. With this deterministic strategy, we hope to enable cell typing throughout development and advance the understanding of both the connectome and the shifts in neural circuitry. S.B. Massachusetts Institute of Technology Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc/4.0/ Deterministic Barcoding of Neuron Identities through Multicolor Fluorescent Markers in C. elegans Thesis application/pdf Bachelor Bachelor of Science in Biological Engineering Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="876cb30a-4b09-4e1d-9ec0-d94901d8e1c3"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Deterministic Barcoding of Neuron Identities through Multicolor Fluorescent Markers in C. elegans</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2023-06</PublicationDate> <Authors> <Author> <DisplayName>Shim, Seung Hyeon</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc/4.0/</License> <Abstract>Mapping the connectivity of neurons, or the brain connectome, with a clear identification of neuron types and functions is a complicated problem that hinders the development of potential therapeutic interventions. Without understanding the identities of neurons that have fundamental roles in neurological or psychiatric disorders, uncovering the disease mechanism and pathology to observe, control, and even repair neural dynamics remains challenging. In this work, we achieve live animal imaging and cell identification by generating a multicolored fluorescent map of different neurons in C. elegans. We take advantage of neuron type-specific promoters to construct transgenes that label each neuron type with unique red, green, and blue fluorescent colors. We also tag subcellular markers of the nucleolus and nuclear membrane with fluorescent proteins to allow for a combinatorial barcode for neuron types, allowing the differentiation of neurons at a single-cell resolution. Through multicolor barcoding of individual neurons, we distinguish different cell types in vivo, helping reconstruct parts of the C. elegans connectome. With this deterministic strategy, we hope to enable cell typing throughout development and advance the understanding of both the connectome and the shifts in neural circuitry.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>