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dc.contributor.advisorHung, Deborah T.
dc.contributor.advisorBlainey, Paul C.
dc.contributor.authorThakku Venkateswaran, Sri Gowtham
dc.date.accessioned2023-01-19T18:50:37Z
dc.date.available2023-01-19T18:50:37Z
dc.date.issued2022-09
dc.date.submitted2022-09-16T18:26:09.664Z
dc.identifier.urihttps://hdl.handle.net/1721.1/147399
dc.description.abstractInfectious diseases continue to represent a significant fraction of worldwide disease burden. A critical part of lowering this burden entails effective testing strategies, as underscored by the ongoing COVID-19 pandemic. The goals of diagnostics, screening, and surveillance have demanded distinct yet innovative approaches to testing. In this work, I present two novel approaches for multiplexed nucleic acid detection (CARMEN and WATSON) that build on the existing CRISPR-diagnostic method SHERLOCK. SHERLOCK combines traditional amplification (PCR or isothermal) with target-specific CRISPR-Cas13 detection and enables new, modular assay designs. With CARMEN, we employ a droplet microfluidic platform to perform thousands of parallel SHERLOCK reactions in nanoliter droplets. CARMEN’s potential for high-throughput infectious disease screening is demonstrated through the design of detection assays for large panels of clinically relevant viral and bacterial pathogens, as well as resistance markers. With WATSON, we maximize the sensitivity of SHERLOCK by targeting multiple tiled regions across a single pathogen genome. The clinical significance of WATSON is demonstrated by applying it to the detection of plasma circulating cell-free DNA in tuberculosis, highlighting its potential as a liquid biopsy test for infectious disease management.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleModular CRISPR-diagnostics for Infectious Diseases
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentHarvard-MIT Program in Health Sciences and Technology
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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