CRISPR Biosensors for Resource-limited Nucleic Acid Detection

To achieve a healthier relationship with our environment and each other, we must continue to improve our ability to rapidly and sensitively monitor pathogens both inside and outside the body. Unfortunately, biological sensing has lagged behind electronic and chemical sensors both in cost and accessibility, primarily due to the need for specialized equipment, sterile work spaces, and sensitive reagents to operate biosensors. The COVID-19 pandemic has only emphasized the need for more sensitive, rapid, and decentralized biosensing solutions that can provide in-the-moment data for personal and public health-related decision making. Recent advances in CRISPR-based biosensors has allowed for a new class of diagnostics with sequence-specific nucleic acid detection capabilities that can provide a rapid response without the need for traditional laboratory infrastructure. The research presented in this dissertation aims to further characterize and expand the applicability of CRISPR-based biosensor systems for resource-limited contexts by non-specialist users. Contributions include a minimally instrumented implementation of a CRISPR-based SHERLOCK assay for rapid and decentralized point-of-care detection of SARS-CoV-2 RNA and variants, a microfluidic platform for SARS-CoV- 2 antibody and CRISPR-based RNA detection through multiplexed electrochemical sensing, and a field-deployable magnetic bead-based waterborne pathogen concentration and CRISPR-based detection system for environmental monitoring. This work also examines how local and indigenous knowledge figure into the conceptualization, collection, and utilization of environmental data within local monitoring programs and considers how novel biosensing tools could generate data at the appropriate resolution for community monitoring needs.

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

• Najjar, Deborah Anne

Advisor dc:contributor.advisor

• Paradiso, Joseph A.

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/1721.1/151976

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151976