Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens
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...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Published: |
Massachusetts Institute of Technology
2022
|
| Online Access: | https://hdl.handle.net/1721.1/140025 https://orcid.org/0000-0001-9655-323X |
| _version_ | 1826207689814835200 |
|---|---|
| author | Anderson, Daniel Allen |
| author2 | Voigt, Christopher A. |
| author_facet | Voigt, Christopher A. Anderson, Daniel Allen |
| author_sort | Anderson, Daniel Allen |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:53:26Z |
| format | Thesis |
| id | mit-1721.1/140025 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:53:26Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1400252022-02-08T03:29:06Z Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens Anderson, Daniel Allen Voigt, Christopher A. Massachusetts Institute of Technology. Department of Biological Engineering 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. Ph.D. 2022-02-07T15:19:41Z 2022-02-07T15:19:41Z 2021-09 2021-11-17T22:09:37.654Z Thesis https://hdl.handle.net/1721.1/140025 https://orcid.org/0000-0001-9655-323X In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Anderson, Daniel Allen Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title | Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title_full | Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title_fullStr | Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title_full_unstemmed | Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title_short | Competition-based CRISPR-dCas9 transcriptional control mechanisms and application of dCas9 biosensors for high-throughput, cell-based protease inhibitor screens |
| title_sort | competition based crispr dcas9 transcriptional control mechanisms and application of dcas9 biosensors for high throughput cell based protease inhibitor screens |
| url | https://hdl.handle.net/1721.1/140025 https://orcid.org/0000-0001-9655-323X |
| work_keys_str_mv | AT andersondanielallen competitionbasedcrisprdcas9transcriptionalcontrolmechanismsandapplicationofdcas9biosensorsforhighthroughputcellbasedproteaseinhibitorscreens |