Document Type
Dissertation - Open Access
Award Date
2022
Degree Name
Doctor of Philosophy (PhD)
Department / School
Biology and Microbiology
First Advisor
Nicholas Butzin
Keywords
Degradation tags, Genetic circuits, Oscillators, Proteases, Proteolytic queueing, Synthetic biology
Abstract
The complexity and redundancy in the network topology of the cell hinder our understanding of the natural system, making it challenging to engineer living organisms with the desired functionality. The long-term goal of synthetic biology and bioengineering is to engineer cells to perform specific functions with increased robustness. The robust engineered systems can be easily applied to different species with the same outcome. An effective approach is a bottom-up approach where we tease apart the biological pathways and study them independently. Understanding the underlying mechanisms of biological pathways can be further applied to construct complex biological circuits that function similarly to natural systems. In this study, I have used the Design-Build-Test-Learn cyclic approach using a widely used organism, E. coli, to engineer synthetic circuits that relied on post-translational, degradation, and transcriptional control. This work is novel because traditional synthetic circuits often rely only on transcriptional control. Synthetic circuits contain engineered genetic frameworks that rely on basic principles of the natural system. I took advantage of the vast knowledge of biological queueing theory to develop robust synthetic circuits. Queueing theory is the study of waiting lines caused due to the bottleneck in the system. It is classically applied to common human activities such as line form (queues) and dissipation at grocery stores, roadways, at the airport, the flow of traffic at traffic signals, etc. Our approach takes the available knowledge we have gained in the macro-world and applies it to the micro (bacteria) and nano-world (proteins, RNA, etc.). The use of queueing theory is explained in detail in Section 1.4. In this study, I examined and utilized the queue formed with proteins at the proteolytic system. Proteases in the cell are limited in numbers (bottleneck) where the queue forms when proteins targeted to proteolysis are waiting in the line to be degraded. I used the understanding of proteolytic queueing and constructed circuits that uses proteolytic queues as a core mechanism. In Chapter 2, I have reviewed the application of proteolytic queueing in synthetic biology, especially in dynamic synthetic oscillators (a review chapter with the most up-todate information). ClpXP proteolytic system is the most explored proteolytic pathway and has been employed in synthetic biology using a well-studied SsrA degradation tag from E. coli. The SsrA tag is a known substrate for ClpXP, and the affinity of the SsrA tag is relatively constant for the ClpXP complex. To acquire a faster degradation rate, I deconstructed and modified the SsrA tag to develop an ultra-high affinity degradation tag (Chapter 3). Faster degradation of tagged protein increases the turnover rate; thus, the processing at the proteolytic queue is faster. However, the specific component of the SspBClpXP proteolytic system causing the queue was unknown, limiting our understanding of the queue complexity. But here, I provide substantial evidence that the ClpX chaperone likely causes queue formation (Chapter 3). I engineered a new synthetic dual-feedback oscillator using this information and the ultra-high affinity tag. This new oscillator dynamic output is unique from previously developed ones (Chapter 4). The understanding of ClpXP proteolytic queueing and synthetic circuits developed in this study can be used to engineer complex circuits for future biotechnology applications.
Library of Congress Subject Headings
Queuing theory.
Synthetic biology.
Biological models.
Number of Pages
119
Publisher
South Dakota State University
Recommended Citation
Jadhav, Prajakta K., "Leveraging Queueing Theory to Develop Advanced Synthetic Biological Circuits" (2022). Electronic Theses and Dissertations. 346.
https://openprairie.sdstate.edu/etd2/346
Included in
Biology Commons, Microbiology Commons, Molecular Biology Commons