ABSTRACT AFROZ, TALIMAN. Understanding and Engineering Individuality in Bacterial Sugar Utilization. (Under the direction of Dr. Chase L. Beisel). Bacteria, like humans, can exhibit ‘individuality’ when faced with similar choices. The presence of positive and negative feedback in regulatory systems plays a crucial role in dictating ‘individuality’ in bacteria. Interestingly, positive and negative feedback loops are also present in sugar utilization pathways ubiquitous to virtually all microorganisms. The bacterial sugar utilization pathways encode regulators, transporters and catabolic enzymes that are induced by their cognate sugars. The regulators control the expression of the pathway components; transporters import more sugar conferring positive feedback and the enzymes break down the sugar imparting negative feedback. Because of scientific and biotechnological implications, sugar utilization pathways in the model bacterium Escherichia coli have been studied for many decades. However, most of the work done so far involved bulk characterization techniques that fail to capture unique behaviors observable only at the single-cell level. The very few single-cell studies available were focused on only two pathways. More importantly, the studies neglected sugar catabolism, which is an integral part of the natural sugar utilization pathways. Therefore, it remains unclear how the myriad of natural sugar utilization pathways respond to sugars at the single-cell level. This thesis work addresses this gap by investigating the single-cell response of E. coli to eight different sugars using a combination of experimental and computational approaches. The response of E. coli to sugars was remarkably diverse, with negative feedback due to catabolism playing a crucial role. Building on these insights, we engineered cells to convert sharp bimodal responses of natural sugar utilization pathways into linear, titratable responses. The motivation behind the work was to use the natural inducible sugar utilization pathways as ‘in-built’ titratable systems in non-model organisms. Using the L-arabinose and D-xylose utilization pathways as model systems, we showed that each modification came with a trade-off. Finally, as an extension to this work we showed how the inadvertent presence of inducer in the medium could affect the response properties such as linearity and dynamic range. Overall, this work provides a few significant insights (a) feedback loops in bacterial sugar utilization are one of the crucial factors that help the cells attain ‘individuality’ or cope under fluctuating nutrient conditions (b) contrary to the prevailing assumptions, response of these ubiquitous utilization pathways can be extremely complex, with potential effects on how the cells can be used for various biotechnological applications (c) the endogenous sugar utilization pathways, with modifications, can be co-opted as titratable systems especially in non-model microorganisms. As part of future work, the strength of the feedbacks loops could be tuned to understand their effects on the transition rates between induced and uninduced states. Also, the single-cell analyses could be extended to microorganisms beyond E. coli to verify the generality of the observed diverse responses. © Copyright 2015 Taliman Afroz All Rights Reserved Understanding and Engineering Individuality in Bacterial Sugar Utilization by Taliman Afroz A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Chemical Engineering Raleigh, North Carolina 2015 APPROVED BY: _______________________________ ______________________________ Dr. Chase L. Beisel Dr. Robert Kelly Committee Chair ________________________________ ________________________________ Dr. Amy Grunden Dr. Jason Haugh DEDICATION This thesis is dedicated to my parents ii BIOGRAPHY Taliman Afroz was born on February 6, 1984 in Dhaka,Bangladesh. After graduating from Maple Leaf International School in 2001, she attended Bangladesh University of Engineering & Technology (BUET) for her undergraduate studies. In 2007, she graduated with her Bachelor of Science in Chemical Engineering from BUET. She worked as a junior lecturer in the department for two years. In the Fall semester of 2009, she joined the Department of Chemical & Biomolecular Engineering at North Carolina State University as a graduate student. After completing her masters degree in two years, she joined the Beisel group in the Spring semester of 2012 to pursue her PhD. iii ACKNOWLEDGMENTS First I would like to thank my advisor Dr Chase L. Beisel for his constant guidance and inspiration. I will always be thankful to him for believing in me and in my abilities. Also, I feel blessed to have such smart, helpful group members who always provided useful insights or constructive criticisms about my work. I gratefully acknowledge the help I got from all the staff of the Chemical & Biomolecular Engineering Department. I would specially like to thank Sandra Bailey for being so nice and helpful. Finally, I would like to thank my parents, brothers and my husband, Rashed, for their unconditional love and support. Last but not the least I would like to thank all those ordinary people of Bangladesh whose tax money helped me to get an almost free education. I will forever be indebted to them. iv TABLE OF CONTENTS LIST OF TABLES - - - - - - - - ix LIST OF FIGURES - - - - - - - - xi Chapter 1 Introduction and Background - - - - - 01 1.1 Individuality in bacteria - - - - - - - - 02 1.2 Bacterial sugar utilization - - - - - - - 03 1.3 Individuality in bacterial sugar utilization? - - - - - 05 1.4 Overview of the thesis - - - - - - - - 11 References - - - - - - - - - - 13 Chapter 2 Understanding and Exploiting Feedback in Synthetic Biology - 21 Abstract - - - - - - - - - - 22 2.1. Introduction - - - - - - - - - 23 2.2. Modes of feedback - - - - - - - - 24 2.2a Transcriptional regulation - - - - - - 24 2.2b Post-transcriptional regulation - - - - - 25 2.2c Post-translational regulation - - - - - - 25 2.2d Cell-cell interactions - - - - - - - 26 2.3. Properties of negative feedback - - - - - - 27 2.3a Dynamics: Shorter response time - - - - - 28 2.3b Steady-state: Linearized response - - - - - 29 2.3c Cell-cell variability: Noise reduction - - - - - 30 2.4. Properties of positive feedback - - - - - - - 33 2.4a Dynamics: Longer response time - - - - - 34 2.4b Steady state: Ultrasensitivity - - - - - - 34 2.4c Cell-cell variability: Increased noise and bistability - - - 35 2.5. Properties of combined negative and positive feedback - - - 37 2.5a Multi-negative feedback loops - - - - - - 37 v 2.5b Layered positive feedback loops - - - - - - 39 2.5c Nested negative and positive feedback loops - - - - 40 2.6 Current applications of feedback in synthetic biology - - - 42 2.6a Metabolic control - - - - - - - 42 2.6b Biosensor design - - - - - - - 44 2.6c Population control - - - - - - - 45 2.7 Future directions - - - - - - - - 49 2.8 Conclusions - - - - - - - - - 50 References - - - - - - - - - - 51 Chapter 3 Bacterial sugar utilization gives rise to distinct single-cell behaviors 59 Abstract - - - - - - - - - - 60 3.1 Introduction - - - - - - - - - 61 3.2 Results - - - - - - - - - - 63 3.2a Varying single-cell behaviors in sugar utilization in E. coli - - 63 3.2b A simple model predicts varying behaviors from the underlying framework - - - - - - - - - 65 3.2c Sugar catabolism allows tunable induction - - - - 69 3.2d Sugar catabolism reduces the extent of hysteresis - - - 72 3.3 Discussion - - - - - - - - - 75 3.4 Experimental procedures - - - - - - - 77 References - - - - - - - - - - 82 Chapter 3 Supplementary information - - - - - - 88 Chapter 4 Trade-offs in engineering sugar utilization pathways for titratable control - - - - - - - - - - 108 Abstract - - - - - - - - - - 109 4.1 Introduction - - - - - - - - - 110 4.2 Results and discussion - - - - - - - - 113 vi 4.2a A simple mathematical model of sugar utilization - - - - 113 4.2b Experimentally probing L-arabinose utilization to explore model predictions - - - - - - - 113 4.2c Constitutively expressing the high-affinity transporter more readily generates a uniform response - - - - - - 116 4.2d Trade-offs when deleting one transporter - - - - 117 4.2e Trade-offs when eliminating sugar catabolism - - - 118 4.2f Breakdown of the sugar can help linearize the response - - 120 4.3 Similar trends when linearizing the response to D-xylose - - - 121 4.4 Design rules to engineer sugar utilization pathways for titratable control - 123 4.5 Methods - - - - - - - - - - 127 References - - - - - - - - - - 131 Chapter 4 Supplementary information - - - - - - 136 Chapter 5 Impact of residual inducer in titratable expression systems - - 153 Abstract - - - - - - - - - - 154 5.1 Introduction - - - - - - - - - 155 5.2 Materials and methods - - - - - - - - 156 5.3 Results - - - - - - - - - - 159 5.3a Mathematical modeling to assess the effects of residual inducer for an inducing system in E. coli - - - - - - - 159 5.3b Experimental verification of the effects of residual inducer for an inducing system in E. coli - - - - - - - - - - 161 5.3c Assessing the effects of residual inducer for a repressing system in E. coli - 162 5.3d Assessing residual inducer for an ‘all-or-none’ response in E. coli - - 164 5.4 Discussion - - - - - - - - - 165 References - - - - - - - - - - 169 Chapter 5 Supplementary information - - - - - - 171 vii Chapter 6 Future work - - - - - - - - 177