The next generations of both biological engineering and computer engineering demand that control be exerted at the molecular level. Creating, characterizing and controlling synthetic biological systems may provide us with the ability to build cells that are capable of a plethora of activities, from computation to synthesizing nanostructures. To develop these systems, we must have a set of tools not only for synthesizing systems, but also designing and simulating them. The BioJADE project provides a comprehensive, extensible design and simulation platform for synthetic biology. BioJADE is a graphical design tool built in Java, utilizing a database back end, and supports a range of simulations using an XML communication protocol. BioJADE currently supports a library of over 100 parts with which it can compile designs into actual DNA, and then generate synthesis instructions to build the physical parts. The BioJADE project contributes several tools to Synthetic Biology. BioJADE in itself is a powerful tool for synthetic biology designers. Additionally, we developed and now make use of a centralized BioBricks repository, which enables the sharing of BioBrick components between researchers, and vastly reduces the barriers to entry for aspiring Synthetic Biologists.

Conditional gene expression systems that enable inducible and reversible transcriptional control are essential research tools and have broad applications in biomedicine and biotechnology. The reverse tetracycline transcriptional activator is a canonical system for engineered gene expression control that enables graded and gratuitous modulation of target gene transcription in eukaryotes from yeast to human cell lines and transgenic animals. However, the system has a tendency to activate transcription even in the absence of tetracycline and this leaky target gene expression impedes its use. Here, we identify single amino acid substitutions that greatly enhance the dynamic range of the system by reducing leaky transcription to undetectable levels while retaining high expression capacity in the presence of inducer. Furthermore, we show that these improved DNA binding domains can be fused to repression domains to create synthetic transcriptional repressors. The function of these transcriptional repressors is dependent on the location of their recruitment and their mechanisms of action.

abstract: RNA aptamers adopt tertiary structures that enable them to bind to specific ligands. This capability has enabled aptamers to be used for a variety of diagnostic, therapeutic, and regulatory applications. This dissertation focuses on the use RNA aptamers in two biological applications: (1) nucleic acid diagnostic assays and (2) scaffolding of enzymatic pathways. First, sensors for detecting arbitrary target RNAs based the fluorogenic RNA aptamer Broccoli are designed and validated. Studies of three different sensor designs reveal that toehold-initiated Broccoli-based aptasensors provide the lowest signal leakage and highest signal intensity in absence and in presence of the target RNA, respectively. This toehold-initiated design is used for developing aptasensors targeting pathogens. Diagnostic assays for detecting pathogen nucleic acids are implemented by integrating Broccoli-based aptasensors with isothermal amplification methods. When coupling with recombinase polymerase amplification (RPA), aptasensors enable detection of synthetic valley fever DNA down to concentrations of 2 fM. Integration of Broccoli-based aptasensors with nucleic acid sequence-based amplification (NASBA) enables as few as 120 copies/mL of synthetic dengue RNA to be detected in reactions taking less than three hours. Moreover, the aptasensor-NASBA assay successfully detects dengue RNA in clinical samples. Second, RNA scaffolds containing peptide-binding RNA aptamers are employed for programming the synthesis of nonribosomal peptides (NRPs). Using the NRP enterobactin pathway as a model, RNA scaffolds are developed to direct the assembly of the enzymes entE, entB, and entF from E. coli, along with the aryl-carrier protein dhbB from B. subtilis. These scaffolds employ X-shaped RNA motifs from bacteriophage packaging motors, kissing loop interactions from HIV, and peptide-binding RNA aptamers to position peptide-modified NRP enzymes. The resulting RNA scaffolds functionalized with different aptamers are designed and evaluated for in vitro production of enterobactin. The best RNA scaffold provides a 418% increase in enterobactin production compared with the system in absence of the RNA scaffold. Moreover, the chimeric scaffold, with E. coli and B. subtilis enzymes, reaches approximately 56% of the activity of the wild-type enzyme assembly. The studies presented in this dissertation will be helpful for future development of nucleic acid-based assays and for controlling protein interaction for NRPs biosynthesis. / Dissertation/Thesis / Doctoral Dissertation Biochemistry 2020

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The bulk of this thesis considers how biological rhythms (oscillators) can be made to synchronize their rhythms by virtue of coupling to an external signal. Such externally controlled synchronization, known as entrainment, is explored using a synthetic biology approach in E.~coli, where I have used rationally designed gene circuits as an experimental model. Two novel modes of entrainment are explored: entrainment by competition between components for degradation, and entrainment by a noisy (aperiodic) stimulus. Both of these modes of entrainment can be shown to strongly synchronize ensembles of synthetic gene oscillators, and thus, these modes of entrainment may be important to understand the appearance of synchrony in natural systems. In addition to the study of entrainment, this thesis contains a general background of relevant material, contributions to the biophysics of multisite proteases, and updated protocols for experimental procedures in microfluidics and microscopy. / Ph. D.

Cellulose, the most abundant biopolymer on earth, is composed of β – 1,4 – linked glucose units, which in turn form a highly ordered crystalline structure that is insoluble and recalcitrant to degradation. It is the world’s most attractive, abundant and renewable energy resource, representing the bioconversion of carbon dioxide into green plants. Cellulosic biomass, such as agricultural and forestry residues, waste paper and industrial waste can therefore be used as an inexpensive and abundantly available source of sugar for fermentation into fuel ethanol. The combustion of biofuels releases carbon dioxide which is thus recycled and hence the use of these fuels in transportation provides an alternative to fossil fuels, solving many environmental problems. The ability to degrade crystalline cellulose seems to be restricted to a specialized group of microorganisms which includes for example Clostridium, Cellulomonas, Cytophaga, Trichoderma etc. Hence the aim of this project was to create BioBricks using different cellulases from cellulose degraders and express them in different expression hosts like Escherichia coli, Bacillus subtilis, Citrobacter freundii etc., using two different promoters, spac and lac. It was observed that the expression of Cytophaga hutchinsonii cellulases (CHU_2103 and CHU_2802) and dehydrogenases (CHU_1944 and CHU_2315) was toxic to the E. coli host for some unknown reason. Therefore it was decided to use cellulases from Cellulomonas fimi, which are well characterized. BioBricks of cellulases (cenA and cex) from C. fimi were introduced into different expression hosts. It was observed that under our experimental conditions Citrobacter freundii SBS197 gave the best results. Both Pspac and Plac were functional in this organism with expression being higher when Pspac was used. When E. coli JM109 was used as an expression host, activity was only detected when the lac promoter was used to control the expression. Although the expression was higher when E. coli JM109 (containing Plac) was used as an expression host, almost all of this activity was residing within the cells, whereas when C. freundii SBS197 was used as an expression host, considerable activity was detected in the surrounding medium, which is essential for cellulose degradation. Growth curve studies were done to see if heterologous cellulases enable the host to use cellulosic substrates as a source of carbon. It was observed that C. freundii SBS197 expressing cenA and cex was able to use filter paper and Avicel as a source of carbon with maximum growth of up to 8.8×108 cfu/ml and 1.2×109 cfu/ml respectively. This was about 2 – 5 fold higher when compared to the control (vector and/or negative) strains. Filter paper completely disappeared within 3 – 4 days when C. freundii SBS197 was used. Slight degradation was observed when E. coli JM109 was used but there was no physical degradation seen when B. subtilis 168 was used as an expression host. Hence it was concluded that heterologous cellulases impart to C. freundii SBS197 with the ability to use cellulosic substrates as a source of carbon. The maximum growth obtained using these cultures is to our knowledge higher than what has been reported so far for recombinant organisms expressing heterologous cellulases using cellulosic substrates as a source of carbon.

Given the explosion in human genetic data, new high-throughput genetic methods are necessary for studying variants and elucidating their role in human disease. In Chapter I, I will expand on this concept and describe current methods for genetically modifying human cells. In E. coli, Multiplex Automatable Genome Engineering (MAGE) is a powerful tool that enables the targeting of multiple genomic loci simultaneously with synthetic oligos that are recombined at high frequencies in an optimized strain. MAGE as a method has two components: organism-specific optimization of oligo recombination parameters and a protein capable of increasing recombination frequencies.

The plant hormone salicylic acid (SA) is an essential activator of plant immune responses directed against biotrophic pathogens. The transcription cofactor NPR1 (Nonexpressor of pathogenesis- related (PR) genes 1) functions to transduce the SA signal into an operational response directed to limited pathogen damage. In the absence of pathogen, NPR1 protein resides in the cytoplasm as a large molecular weight oligomer held together by disulphide bonding. Initiation of defence signalling leads to changes in intracellular redox conditions that promote NPR1 momomer release. Translocation of monomeric NPR1 to the nucleus results in the activation of over 2200 immune-related genes in Arabidopsis. NPR1 lacks a canonical DNA-binding domain but is known to perform part of its regulatory function through engagement of TGA factors (bZIP transcription factor). Induction of SA-dependent signalling is invariably associated with PR-1 gene expression and accumulation of mRNA for this gene serves as a useful marker of defence activation. However, both functional redundancy and stochastic factors limit the effectiveness of standard genetic approaches used in plant research, and thus much of the hierarchal processes surrounding NPR1-dependent gene activation are not fully understood. Using a synthetic biology approach we aim to complete exploratory work and set the foundations for the development of a yeast tool that can be used to manipulate and subsequently understand NPR1 function in relation to interacting partners and gene activation. Accordingly, using this tool we sought to create a conceptual protein circuit based on theoretical plant immunity. In completing this work we have developed a Saccharomyces cerevisiae strain that exhibits a highly oxidising intracellular redox environment. This was achieved by knocking out genes encoding S-nitrosoglutathione reductase (SFA1), flavohemoglobin (YHB1) and YAP1 (bZIP transcription factor), all important components in regulating cellular redox homeostasis and protein S-nitrosylation state in S. cerevisiae. Characterisation of this cell (designated Δsfa1yap1yhb1) reveals a high tolerance to such redox perturbations. Importantly, NPR1 is by default, assembled predominantly in the oligomeric form in this biological chassis. By activating two inducible inputs in the form of Arabidopsis S-nitrosoglutathione reductase (AtGSNOR) and Thioredoxin (AtTRXh5) which both function to promote NPR1 monomerisation, we have created a switch to selectively control NPR1 oligomer-monomer equilibrium. To complete the synthetic circuit, TGA3 was included, along with a modified yeast MEL1 promoter that has been customised to contain the TGA-responsive upstream activation sequence (termed the as-1 element) present in the promoter region of the PR-1 gene. Using FRET tools we were able to confirm nuclear interaction between monomeric NPR1 and TGA3, with this association appearing to induce as-1 element binding. However this process is not sufficient to activate a Luciferase (LUC) reporter gene, even when the GAL4 activation domain (GAL4 AD) is fused to NPR1. Ordinarily, a CUL3-dependent proteolysis-coupled transcription cycle is necessary to maintain efficient NPR1-dependent gene transcription in Arabidopsis. Although S. cerevisiae encodes an evolutionarily related CUL3 ortholog, examination by western blot demonstrates that NPR1 protein is stable in this cell, indicating an endogenous mechanism to degrade NPR1 is either not present or not functional in yeast. As such, this synthetic yeast tool represents a completely novel approach to identify missing components functioning in NPR1-mediated transcriptional regulation. Furthermore, in collaboration with a skilled bioinformatician, and using a rule-based stochastic modeling tool known as Kappa, we have been able to develop, for the first time, a preliminary mathematical simulation representative of NPR1-dependent gene activation that can be used as a foundation for future works.

Current biofuel production methods use engineered bacteria to break down cellulose and convert it to biofuel. However, this production is limited by the toxicity of the biofuel to the organism that is producing it. Therefore, to increase yields, microbial biofuel tolerance must be increased. Tolerant strains of bacteria use a wide range of mechanisms to counteract the detrimental effects of toxic solvents. Previous research demonstrates that efflux pumps are effective at increasing tolerance to various biofuels. However, when overexpressed, efflux pumps burden cells, which hinders growth and slows biofuel production. Therefore, the toxicity of the biofuel must be balanced with the toxicity of pump overexpression. We have developed a mathematical model and experimentally characterized parts for a synthetic feedback loop to control efflux pump expression so that it is proportional to the concentration of biofuel present. In this way, the biofuel production rate will be maximal when the concentration of biofuel is low because the cell does not expend energy expressing efflux pumps when they are not needed. Additionally, the microbe is able to adapt to toxic conditions by triggering the expression of efflux pumps, which allows it to continue biofuel production. The mathematical model shows that this feedback loop increases biofuel production relative to a model that expresses efflux pumps at a constant level by delaying pump expression until it is needed. This result is more pronounced when there is variability in biofuel production rates because the system can use feedback to adjust to the actual production rate. To complement the mathematical model, we also constructed a whole cell biosensor that responds to biofuel by expressing a fluorescent reporter protein from a promoter under the control of the sensor.

One major challenge in synthetic biology is how to design genetic circuits with predictable behaviors in various biological contexts. There are two limitations to addressing this challenge in mammalian cells. First, models that can predict circuit behaviors accurately in bacteria cells cannot be directly translated to mammalian cells. Second, upon interconnection, the behavior of a module, the building block of a circuit, may be different from its behavior in a standalone setting. In this thesis, I present a bottom-up modeling framework that can be used to predict circuit behaviors in transiently transfected mammalian cells (TTMC). The first part of the framework is based on a novel bin-dependent ODE model that can describe the behavior of modules in TTMC accurately. The second part of the framework rests upon a method of modular composition that allows model-based design of circuits. The efficacies of the bin-dependent model and the method of modular composition are validated via experimental data. The effects of retroactivity, a loading effect that arises from modular composition, on circuit behaviors are also investigated.