{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/140025"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/140025","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens","abstract":"Catalytically-dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. In Chapter 1 of this thesis, I outline the multitude of tools and applications that have been developed for dCas9 circuits. I then discuss the limitations and advantages of these systems and and outline some of the most promising opportunities for dCas9-based genetic circuits. In Chapter 2, I devise, model, and implement a new-to-nature transcriptional control mechanism using dCas9. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one transcription factor can augment the activity of another. Here, I implement this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. I demonstrate that this mechanism can control both transcriptional initiation and transcriptional elongation with over 30-fold dynamic range. This work characterizes and demonstrates a new genetic control modality that could be used to build analog circuits or to implement cis-regulatory logic on CRISPRi-targeted native genes. In the final chapter of this thesis, I use a dCas9 genetic circuit to create an in vivo selection system for protease inhibitors. By leveraging a previously-described dCas9 toolkit, I create a synthetic genetic circuit that responds to SARS-CoV-2 viral protease activity. Using this circuit as an in vivo biosensor, I integrate it with a RiPP-based molecular library and an in vivo selection system to screen for inhibitors of the SARS-CoV-2 Papain-like protease (PLpro). With this integrated system, I screened tens of millions of RiPPs and identified DAA680, a 13-AA modified peptide with PLpro inhibitory activity. However, follow-up studies showed that this peptide also inhibits another SARS-CoV-2 viral protease, CLpro, indicating a non-specific mechanism of inhibition. Nonetheless, these results validate our system’s ability to identify and isolate RiPP-based protease inhibitors from large libraries. Additionally, our extensive characterization of the selection system should be generalizable to any biosensor with a transcriptional output. This should enable the rapid deployment of novel cell-based selection methods that can identify molecules with diverse bioactivities.","abstract_html":"Catalytically-dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. In Chapter 1 of this thesis, I outline the multitude of tools and applications that have been developed for dCas9 circuits. I then discuss the limitations and advantages of these systems and and outline some of the most promising opportunities for dCas9-based genetic circuits. In Chapter 2, I devise, model, and implement a new-to-nature transcriptional control mechanism using dCas9. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one transcription factor can augment the activity of another. Here, I implement this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. I demonstrate that this mechanism can control both transcriptional initiation and transcriptional elongation with over 30-fold dynamic range. This work characterizes and demonstrates a new genetic control modality that could be used to build analog circuits or to implement cis-regulatory logic on CRISPRi-targeted native genes. In the final chapter of this thesis, I use a dCas9 genetic circuit to create an in vivo selection system for protease inhibitors. By leveraging a previously-described dCas9 toolkit, I create a synthetic genetic circuit that responds to SARS-CoV-2 viral protease activity. Using this circuit as an in vivo biosensor, I integrate it with a RiPP-based molecular library and an in vivo selection system to screen for inhibitors of the SARS-CoV-2 Papain-like protease (PLpro). With this integrated system, I screened tens of millions of RiPPs and identified DAA680, a 13-AA modified peptide with PLpro inhibitory activity. However, follow-up studies showed that this peptide also inhibits another SARS-CoV-2 viral protease, CLpro, indicating a non-specific mechanism of inhibition. Nonetheless, these results validate our system’s ability to identify and isolate RiPP-based protease inhibitors from large libraries. Additionally, our extensive characterization of the selection system should be generalizable to any biosensor with a transcriptional output. This should enable the rapid deployment of novel cell-based selection methods that can identify molecules with diverse bioactivities.","abstract_has_math":false,"creators":["Anderson, Daniel Allen"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Biological Engineering","school":null,"contributors":[],"advisors":["Voigt, Christopher A."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09","date_published":"2021-09","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/1721.1/140025","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Voigt, Christopher A."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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In Chapter 1 of this thesis, I outline the multitude of tools and applications that have been developed for dCas9 circuits. I then discuss the limitations and advantages of these systems and and outline some of the most promising opportunities for dCas9-based genetic circuits. In Chapter 2, I devise, model, and implement a new-to-nature transcriptional control mechanism using dCas9. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one transcription factor can augment the activity of another. Here, I implement this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. I demonstrate that this mechanism can control both transcriptional initiation and transcriptional elongation with over 30-fold dynamic range. This work characterizes and demonstrates a new genetic control modality that could be used to build analog circuits or to implement cis-regulatory logic on CRISPRi-targeted native genes. In the final chapter of this thesis, I use a dCas9 genetic circuit to create an in vivo selection system for protease inhibitors. By leveraging a previously-described dCas9 toolkit, I create a synthetic genetic circuit that responds to SARS-CoV-2 viral protease activity. Using this circuit as an in vivo biosensor, I integrate it with a RiPP-based molecular library and an in vivo selection system to screen for inhibitors of the SARS-CoV-2 Papain-like protease (PLpro). With this integrated system, I screened tens of millions of RiPPs and identified DAA680, a 13-AA modified peptide with PLpro inhibitory activity. However, follow-up studies showed that this peptide also inhibits another SARS-CoV-2 viral protease, CLpro, indicating a non-specific mechanism of inhibition. Nonetheless, these results validate our system’s ability to identify and isolate RiPP-based protease inhibitors from large libraries. Additionally, our extensive characterization of the selection system should be generalizable to any biosensor with a transcriptional output. This should enable the rapid deployment of novel cell-based selection methods that can identify molecules with diverse bioactivities."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens"]}]}],"canonical_facts":{"dc:contributor.advisor":["Voigt, Christopher A."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Biological Engineering"],"dc:creator":["Anderson, Daniel Allen"],"dc:date.accessioned":["2022-02-07T15:19:41Z"],"dc:date.available":["2022-02-07T15:19:41Z"],"dc:date.issued":["2021-09"],"dc:description.abstract":["Catalytically-dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. In Chapter 1 of this thesis, I outline the multitude of tools and applications that have been developed for dCas9 circuits. I then discuss the limitations and advantages of these systems and and outline some of the most promising opportunities for dCas9-based genetic circuits. In Chapter 2, I devise, model, and implement a new-to-nature transcriptional control mechanism using dCas9. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one transcription factor can augment the activity of another. Here, I implement this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. I demonstrate that this mechanism can control both transcriptional initiation and transcriptional elongation with over 30-fold dynamic range. This work characterizes and demonstrates a new genetic control modality that could be used to build analog circuits or to implement cis-regulatory logic on CRISPRi-targeted native genes. In the final chapter of this thesis, I use a dCas9 genetic circuit to create an in vivo selection system for protease inhibitors. By leveraging a previously-described dCas9 toolkit, I create a synthetic genetic circuit that responds to SARS-CoV-2 viral protease activity. Using this circuit as an in vivo biosensor, I integrate it with a RiPP-based molecular library and an in vivo selection system to screen for inhibitors of the SARS-CoV-2 Papain-like protease (PLpro). With this integrated system, I screened tens of millions of RiPPs and identified DAA680, a 13-AA modified peptide with PLpro inhibitory activity. However, follow-up studies showed that this peptide also inhibits another SARS-CoV-2 viral protease, CLpro, indicating a non-specific mechanism of inhibition. Nonetheless, these results validate our system’s ability to identify and isolate RiPP-based protease inhibitors from large libraries. Additionally, our extensive characterization of the selection system should be generalizable to any biosensor with a transcriptional output. This should enable the rapid deployment of novel cell-based selection methods that can identify molecules with diverse bioactivities."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/140025"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"dc:rights.uri":["http://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens"],"dc:type":["Thesis"],"thesis:degree_name":["Doctoral","Doctor of Philosophy"]},"updated_at":"2026-07-22T22:21:55Z"}