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Genetic Circuits for the Control of Multi-Strain Bacterial Populations

Citation

McCardell, Reed Dillard (2021) Genetic Circuits for the Control of Multi-Strain Bacterial Populations. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/wgpp-vj97. https://resolver.caltech.edu/CaltechTHESIS:05082021-185615529

Abstract

Microbial species rarely exist alone. Nearly everywhere you could think to look, microorganisms of various species live together in harmony. Microbes together in their communities are incredibly powerful actors wherever they are found; they perform small miracles---the conversion of milk into yogurt---and large ones---production of most of the planet's oxygen and organic carbon.

Our burgeoning knowledge of microbial life combined with modern technologies to manipulate it create a critical, exciting opportunity to harness microbial power for the betterment of technology, people, and the planet. This thesis presents a body of work which explores the manipulation of microbial communities using the intersectional bio-engineering approach of synthetic biology. We demonstrate how molecular tools evolved by bacteria can be repurposed to create rationally designed systems for controlling features of bacterial populations.

We begin by examining a genetic circuit that caps the size of a bacterial population by coordinating the deaths of population members -- the population capping or "pop cap" circuit. Briefly, E. coli cells in the pop cap circuit are engineered to synthesize a chemical -- a quorum sensing (QS) signal -- that reports the density of the population, sense this chemical, and produce the ccdB toxin to destroy themselves in response. The molecular tools that make up this circuit are drawn from organisms across the spectrum of bacterial diversity. Brought together, they create a feedback control circuit that controls population size by causing member cells to die when a target population size has been reached. To improve the performance of this population controller and reduce the influence of the environment on the circuit, we add the aiiA quorum sensing signal degradase to allow the experimenter control over the degradation rate of the QS density signal. Additionally, we explore RNA and protein mechanisms to sequester the death-causing toxin---inactivating it---allowing us to release a population cap. The resulting "cap and release" circuit is a flexible motif that can be scaled to control multi-strain populations, expanding the scope of control beyond the single-strain populations regulated by the base pop cap circuit.

Using the scalable cap and release motif, we design a genetic circuit to regulate a multi-strain community. Two different cell strains expressing symmetric, interconnected cap and release systems form the "A=B" circuit, so named for its ability to control the composition of the community to a target ratio of A cells to B cells, or Apopulation = αBpopulation. Through dynamical system models of the system, we explore the effects of active QS signal degradation on composition control performance and perform a parameter sensitivity analysis of the system to help determine the best method for building a functioning A=B system in the laboratory. We use a high throughput construction and screening protocol to create variants of the A=B system with identical architectures, but slightly differing component production rates. We crown the most successful variant with a series of experiments to determine if it indeed recapitulates our model's predictions for its performance. Our implementation of the A=B circuit can successfully regulate the composition of a community, with interesting additional effects on total population density.

The cap and release and A=B circuits need parts that can do three things: 1) send a signal between cells to communicate information, 2) compare two signals, 3) regulate cell growth or death. We highlight bacteriocins, bacterial protein exotoxins that are released from a producer cell to kill other cells of similar species, as attractive tools for bacterial community engineering both for their multi-functionality and modular protein structure. By themselves, bacteriocins can perform all the functions needed for population control: they transmit themselves between cells, have unique high-affinity sequestering antitoxin proteins, and are toxins to receiver cells. We begin the process of their characterization and usage as synthetic biological "parts" by creating non-native expression systems that match native expression strengths. Using these experimenter-controlled systems we design preliminarily test a bacteriocin-based bacterial community control circuit. Additionally, given the E. coli colicin bacteriocins' unique, nearly plug-and-play modular domain structure, we explore possibilities for engineering colicin proteins themselves for increased functional diversity or uses outside of growth regulation.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Synthetic biology; microbial communities; population control; bioengineering; genetic engineering; synthetic ecology
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Murray, Richard M.
Thesis Committee:
  • Pierce, Niles A. (chair)
  • Orphan, Victoria J.
  • Ismagilov, Rustem F.
  • Murray, Richard M.
Defense Date:26 April 2021
Non-Caltech Author Email:reedmccardell (AT) gmail.com
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechTHESIS:05082021-185615529
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:05082021-185615529
DOI:10.7907/wgpp-vj97
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/225045DOIArticle adapted for chapter 2.
https://doi.org/10.1101/632174UNSPECIFIEDArticle adapted for chapter 3.
ORCID:
AuthorORCID
McCardell, Reed Dillard0000-0002-0955-3133
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14138
Collection:CaltechTHESIS
Deposited By: Reed McCardell
Deposited On:21 May 2021 23:40
Last Modified:28 May 2021 17:12

Thesis Files

[img] PDF (Complete thesis) - Final Version
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[img] PDF (Chapter 1 - Introduction) - Final Version
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[img] PDF (Chapter 2 - First Research Content Chapter) - Final Version
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[img] PDF (Chapter 3) - Final Version
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[img] PDF (Chapter 4) - Final Version
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[img] PDF (Chapter 5) - Final Version
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