Highly multiplexed molecular mapping of biological samples via integrated experimental and computational technologies

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.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Program in Media Arts and Sciences (Massachusetts Institute of Technology)

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Goodwin, Daniel Robert

Advisor dc:contributor.advisor

• Boyden, Edward S.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/143366

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/143366