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Engineering Conditional Guide RNAs for Cell-Selective Regulation of CRISPR/Cas9

Citation

Chen, Zhewei (2023) Engineering Conditional Guide RNAs for Cell-Selective Regulation of CRISPR/Cas9. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/cajs-d417. https://resolver.caltech.edu/CaltechTHESIS:12022022-010002116

Abstract

CRISPR/Cas9 is a versatile platform for implementing diverse modes of genetic perturbation such as gene silencing, induction, deletion, or replacement. This technology is popularly used in developmental biology to probe genetic circuitry via constitutive gene knockdown. Global gene silencing could introduce artifacts in the study of developmental regulatory pathways, and this motivates the development of cell-selective gene editing. Our lab has recently created conditional guide RNAs (cgRNA) that enable CRISPR/Cas9 systems to silence a desired gene Y conditioned on the detection of an RNA transcript X inside of a cell. cgRNA systems were discovered via insertion and deletion mutations that systematically explored the structure function of the guide RNA. Nucleic acid engineering software (NUPACK) was used to generate orthogonal libraries of cgRNA molecules that executed both ON → OFF logic (conditional inactivation by an RNA trigger) and OFF → ON logic (conditional activation by an RNA trigger). A dCas9-based RFP silencing assay in bacteria was developed and used to show these cgRNA sequences were functional and could detect short exogenous trigger sequences in an orthogonal and doseresponsive manner. Subsequent studies on cgRNA structure and function enabled us to engineer next-generation systems that have fewer constraints on the trigger sequence or structure. These next-generation cgRNAs were tested against short synthetic mRNA transcripts, truncated sub-sequences of endogenous mRNAs, and full-length endogenous mRNAs. Synthetic mRNA transcripts were used to study the effect of protein translation on trigger RNA binding. cgRNAs were capable of detecting synthetic sequences embedded in the 3′ UTR of fluorescent protein mRNAs. cgRNAs could also detect short synthetic mRNAs or truncated subsequences from endogenous mRNAs. However, the detection of native full-length endogenous mRNAs remained challenging because we cannot reliably predict the local structure of sub-sequences within a long RNA transcript. High-throughput cgRNAscreening may prove necessary for finding accessible binding sites onmRNA transcripts. Nevertheless, cgRNA functionalities could be useful in developmental biology by enabling precision perturbation of regulatory events, linking guide RNA activity to an RNA marker X correlated to a specific cell type or temporal expression pattern. This work opens the possibility for future applications such as cell-selective gene therapies.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:nucleic acid nanotechnology CRISPR Cas9 RNA engineering
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Pierce, Niles A.
Thesis Committee:
  • Murray, Richard M. (chair)
  • Rothemund, Paul W. K.
  • Hay, Bruce A.
  • Pierce, Niles A.
Defense Date:15 December 2022
Non-Caltech Author Email:zchen (AT) alumni.caltech.edu
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008; the findings are those of the authors and should not be interpreted as representing the official views or policies of the US Government
Rosen Bioengineering CenterUNSPECIFIED
Molecular Programming Project (NSF)NSF-CCF-1317694
Resnick Sustainability InstituteUNSPECIFIED
Biotechnology Leadership Program (National Institute of General Medical Sciences)NIH-T32GM112592A
Record Number:CaltechTHESIS:12022022-010002116
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:12022022-010002116
DOI:10.7907/cajs-d417
Related URLs:
URLURL TypeDescription
https://doi.org/10.1021/acscentsci.9b00340DOIArticle adapted for ch. 2
ORCID:
AuthorORCID
Chen, Zhewei0000-0002-7422-095X
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:15070
Collection:CaltechTHESIS
Deposited By: Zhewei Chen
Deposited On:24 Mar 2023 17:31
Last Modified:08 Nov 2023 00:43

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