{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/143366"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/143366","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Highly multiplexed molecular mapping of biological samples via integrated experimental and computational technologies","abstract":"Identification and labeling of diverse molecular identities in biological samples has traditionally come at a price of decreased spatial information. Electron microscopy, with its nanometer spatial resolution and excellent ultrastructure preservation, yet essentially no molecular identification, is the most obvious example of this dichotomy that pervades all imaging paradigms. The Boyden Lab has previously developed Expansion Microscopy (ExM), which increases both spatial resolution of fluorescence imaging and target accessibility via isotropically expandable hydrogels. While proteomicbased approaches have the bottleneck of antibodies, nucleic acid sequencing is universally applicable to every molecular target and provides for uniform sample handling and essentially infinite multiplexing. In this thesis, I present the development of the Expansion Sequencing (ExSeq) technology suite, which resolves the underlying tensions between molecular, spatial, and ultrastructural information by multiplexing in situ sequencing and protein information in single, intact specimens. ExSeq produces high-resolution transcriptomic maps of intact tissues and is sensitive enough to detect thousands of different genes within a single sample. Applied to the mouse hippocampus, ExSeq produces transcriptomic atlases of diverse cell types and visualizes mRNA transcript content across thousands of dendritic spines of single CA1 pyramidal neurons. ExSeq also reveals the molecular organization and position-dependent states of many cells in a human metastatic breast cancer sample from a patient. ExSeq harnesses novel experimental and computational techniques to systematically encode and decode biological information from the microscope. I conclude with an exploration of ExSeq as a platform technology for molecular connectomics, with an eye toward robust and democratizeable synaptic-scale maps of the brain.","abstract_html":"Identification and labeling of diverse molecular identities in biological samples has traditionally come at a price of decreased spatial information. Electron microscopy, with its nanometer spatial resolution and excellent ultrastructure preservation, yet essentially no molecular identification, is the most obvious example of this dichotomy that pervades all imaging paradigms. The Boyden Lab has previously developed Expansion Microscopy (ExM), which increases both spatial resolution of fluorescence imaging and target accessibility via isotropically expandable hydrogels. While proteomicbased approaches have the bottleneck of antibodies, nucleic acid sequencing is universally applicable to every molecular target and provides for uniform sample handling and essentially infinite multiplexing. In this thesis, I present the development of the Expansion Sequencing (ExSeq) technology suite, which resolves the underlying tensions between molecular, spatial, and ultrastructural information by multiplexing in situ sequencing and protein information in single, intact specimens. ExSeq produces high-resolution transcriptomic maps of intact tissues and is sensitive enough to detect thousands of different genes within a single sample. Applied to the mouse hippocampus, ExSeq produces transcriptomic atlases of diverse cell types and visualizes mRNA transcript content across thousands of dendritic spines of single CA1 pyramidal neurons. ExSeq also reveals the molecular organization and position-dependent states of many cells in a human metastatic breast cancer sample from a patient. ExSeq harnesses novel experimental and computational techniques to systematically encode and decode biological information from the microscope. I conclude with an exploration of ExSeq as a platform technology for molecular connectomics, with an eye toward robust and democratizeable synaptic-scale maps of the brain.","abstract_has_math":false,"creators":["Goodwin, Daniel Robert"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Program in Media Arts and Sciences (Massachusetts Institute of Technology)","school":null,"contributors":[],"advisors":["Boyden, Edward S."],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-02","date_published":"2022-02","updated_at":"2026-07-22T22:21:55Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"rights_urls":["http://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/143366","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Boyden, Edward S."]},{"key":"dc:contributor.department","label":"Department","values":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"]},{"key":"dc:creator","label":"Author","values":["Goodwin, Daniel Robert"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-06-15T13:15:35Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-06-15T13:15:35Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-02"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctoral","Doctor of Philosophy"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright MIT"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/143366"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Identification and labeling of diverse molecular identities in biological samples has traditionally come at a price of decreased spatial information. Electron microscopy, with its nanometer spatial resolution and excellent ultrastructure preservation, yet essentially no molecular identification, is the most obvious example of this dichotomy that pervades all imaging paradigms. The Boyden Lab has previously developed Expansion Microscopy (ExM), which increases both spatial resolution of fluorescence imaging and target accessibility via isotropically expandable hydrogels. While proteomicbased approaches have the bottleneck of antibodies, nucleic acid sequencing is universally applicable to every molecular target and provides for uniform sample handling and essentially infinite multiplexing. In this thesis, I present the development of the Expansion Sequencing (ExSeq) technology suite, which resolves the underlying tensions between molecular, spatial, and ultrastructural information by multiplexing in situ sequencing and protein information in single, intact specimens. ExSeq produces high-resolution transcriptomic maps of intact tissues and is sensitive enough to detect thousands of different genes within a single sample. Applied to the mouse hippocampus, ExSeq produces transcriptomic atlases of diverse cell types and visualizes mRNA transcript content across thousands of dendritic spines of single CA1 pyramidal neurons. ExSeq also reveals the molecular organization and position-dependent states of many cells in a human metastatic breast cancer sample from a patient. ExSeq harnesses novel experimental and computational techniques to systematically encode and decode biological information from the microscope. I conclude with an exploration of ExSeq as a platform technology for molecular connectomics, with an eye toward robust and democratizeable synaptic-scale maps of the brain."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Highly multiplexed molecular mapping of biological samples via integrated experimental and computational technologies"]}]}],"canonical_facts":{"dc:contributor.advisor":["Boyden, Edward S."],"dc:contributor.department":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"],"dc:creator":["Goodwin, Daniel Robert"],"dc:date.accessioned":["2022-06-15T13:15:35Z"],"dc:date.available":["2022-06-15T13:15:35Z"],"dc:date.issued":["2022-02"],"dc:description.abstract":["Identification and labeling of diverse molecular identities in biological samples has traditionally come at a price of decreased spatial information. 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ExSeq produces high-resolution transcriptomic maps of intact tissues and is sensitive enough to detect thousands of different genes within a single sample. Applied to the mouse hippocampus, ExSeq produces transcriptomic atlases of diverse cell types and visualizes mRNA transcript content across thousands of dendritic spines of single CA1 pyramidal neurons. ExSeq also reveals the molecular organization and position-dependent states of many cells in a human metastatic breast cancer sample from a patient. ExSeq harnesses novel experimental and computational techniques to systematically encode and decode biological information from the microscope. 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