NSF Org:	MCB Div Of Molecular and Cellular Bioscience
Recipient:	UNIVERSITY OF WASHINGTON
Initial Amendment Date:	August 9, 2022
Latest Amendment Date:	July 6, 2023
Award Number:	2225632
Award Instrument:	Standard Grant
Program Manager:	Anthony Garza aggarza@nsf.gov  (703)292-2489 MCB  Div Of Molecular and Cellular Bioscience BIO  Direct For Biological Sciences
Start Date:	August 15, 2022
End Date:	July 31, 2025 (Estimated)
Total Intended Award Amount:	$671,552.00
Total Awarded Amount to Date:	$689,062.00
Funds Obligated to Date:	FY 2022 = $671,552.00 FY 2023 = $17,510.00
History of Investigator:	Jesse Zalatan (Principal Investigator) zalatan@uw.edu James Carothers (Co-Principal Investigator)
Recipient Sponsored Research Office:	University of Washington 4333 BROOKLYN AVE NE SEATTLE WA  US  98195-1016 (206)543-4043
Sponsor Congressional District:	07
Primary Place of Performance:	University of Washington 4333 Brooklyn Ave NE Seattle WA  US  98195-0001
Primary Place of Performance Congressional District:	07
Unique Entity Identifier (UEI):	HD1WMN6945W6
Parent UEI:
NSF Program(s):	Systems and Synthetic Biology
Primary Program Source:	01002324DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	7465, 9251
Program Element Code(s):	801100
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.074

ABSTRACT

This project seeks to develop new tools to regulate bacterial gene expression for biosynthesis. Dramatic successes in metabolic engineering have been achieved through laborious efforts to optimize gene expression for the production of high-value chemicals. Programmable, DNA-targeting CRISPR-Cas tools can be used to rapidly implement complex genetic programs, but in bacteria these systems have limitations in their ability to precisely control individual genes. To improve the ability to precisely control cellular behavior, the investigators will develop RNA-targeting CRISPR-Cas systems that act post-transcriptionally and may overcome the limitations of the DNA-targeting systems. The sophisticated control systems developed in this project will be useful for practical biosynthesis, bacterial engineering, and basic research in bacteria. These findings will be incorporated into educational materials and courses taught to chemistry and engineering students. This project will also provide opportunities for underrepresented students at the high school and undergraduate levels to participate in laboratory research.


Bacterial metabolic pathways perform complex chemical transformations with high specificity to produce biosynthetic products. Introducing heterologous genes allows metabolism to be diverted to new synthetic targets, but optimizing the function of these engineered strains is challenging. The goal of this proposal is to develop a new class of bacterial RNA-targeting tools to systematically regulate multi-gene expression programs, and to identify regulatory architectures that can improve the output of biosynthetic pathways. Previously, DNA-targeting CRISPR-Cas transcriptional regulatory circuits have been successfully assembled into sophisticated multi-gene regulatory programs. Despite their enormous potential, DNA-targeting CRISPR-Cas systems have important limitations in their ability to precisely up- or down-regulate individual bacterial gene targets. For this project, the investigators will create dCas13-based RNA-targeting tools, which act post-transcriptionally and may overcome the limitations of DNA-targeting CRISPR-Cas systems. The immediate goal of the project is to develop new capabilities for gene repression and activation at the translational level. First, the investigators will use Agile BioFoundry (ABF) capabilities to learn global rules for dCas13-mediated translational regulation of gene expression and metabolic flux in bacteria. Next, they will systematically compare dCas13-mediated translational regulation to dCas9-mediated transcriptional control to determine whether these systems can produce distinct functional effects. Finally, they will demonstrate the utility of this knowledge by implementing translational control systems in Design-Build-Test-Learn (DBTL) cycles applied to engineer aromatic biosynthesis in a non-model microbe that can be used for industrial bioproduction. These systems will further expand the toolkit for exploring the large space of regulatory architectures to optimize bacterial biosynthesis.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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