The field of Synthetic Biology seeks to develop engineering principles for biological systems. Modular biological parts are repurposed and recombined to develop new synthetic biological devices with novel functions. The proper functioning of these devices is dependent on the cellular context provided by the host organism, and the interaction of these devices with host systems. The field of Systems Biology seeks to measure and model the properties of biological phenomena at the network scale. We present the application of systems biology approaches to synthetic biology, with particular emphasis on understanding and remodeling metabolic networks. Chapter 2 demonstrates the use of a Flux Balance Analysis model of the Saccharomyces cerevisiae metabolic network to identify and construct strains of S. cerevisiae that produced increased amounts of formic acid. Chapter 3 describes the development of synthetic metabolic pathways in Escherichia coli for the production of hydrogen, and a directed evolution strategy for hydrogenase enzyme improvement. Chapter 4 introduces the use of metabolomic profiling to investigate the role of circadian regulation in the metabolic network of the photoautotrophic cyanobacterium Synechococcus elongatus PCC 7942. Together, this work demonstrates the utility of network-scale approaches to understanding biological systems, and presents novel strategies for engineering metabolism.

In response to osmotic shock in Saccharomyces cerevisiae the MAP kinase Hog1 coordinates a large-scale transcriptional stress response, rapidly producing hundreds of copies of specified transcripts. Many of the most highly induced genes are bound and regulated by a transcription factor, Sko1, but lack the canonical binding site for this factor. We use ChIP-seq to demonstrate a stress-specific binding mode of Sko1. In stress, Sko1 binds to promoters in close proximity to Hog1, and another Hog1-regulated transcription factor, Hot1. This mode of Sko1 binding requires the physical presence of Hog1, but not Hog1 phosphorylation of Sko1. We identify candidate Sko1 and Hot1 binding motifs that predict co-localization of Sko1, Hot1, and Hog1 at promoters. We then demonstrate a role for Sko1 and Hot1 in directing Hog1-associated RNA Pol II to target genes, where Hog1 is present with the elongating polymerase. We suggest a possible model for Hog1 reprogramming of transcription in the early stages of the osmotic stress response. We then determine the extent and structure of the Hog1 controlled transcriptional program in a related stress, damage to the cell wall. We find that Sko1 and Hot1 have different apparent thresholds for activation by Hog1. In addition, in cell wall damage, Hog1 regulates an additional transcription factor, Rlm1, that is not involved in other Hog1 regulated stress responses. This factor is activated by the coincidence of a signal from Hog1 with that of another MAP kinase, Slt2.

Levels of macromolecules fluctuate both spatially and temporally in individual cells. Such heterogeneity could be exploited for bet hedging in uncertain environments, or be suppressed by negative feedback if perturbations are deleterious. For the master stress-response regulator in Escherichia coli, RpoS, both of these scenarios have been suggested. RpoS levels are also exceedingly low and controlled by the ClpXP protease, which reportedly displays extreme spatial heterogeneity. However, little is known quantitatively about RpoS dynamics. This is partly because no functional protein fusions exist, but also because the quantitative tools for studying fluctuations and localizations are limited, particularly ones that can be independently validated. Here I develop such methods and begin applying them to RpoS. Protein localization measurements increasingly rely on fluorescent protein fusions and are difficult to verify independently. I designed a non-intrusive method for validating localization patterns in live bacterial cells by exploiting post-division heterogeneity in downstream processes. Applying this assay to the ClpXP protease, widely reported to form biologically relevant foci, revealed in fact that the protease molecules are not specifically localized inside cells, as confirmed by four independent methods. I further evaluated 20+ commonly used fluorescent reporters and found that many cause severe mislocalization when fused to homo-oligomers, likely due to avidity effects. Further reinvestigating other foci-forming proteins strongly suggests that the previously reported foci were all caused by the fluorescent proteins used. For mRNAs – which are often present in low numbers per cell and major sources of non-genetic heterogeneity – existing single-cell assays have unknown accuracy: the experimental counting errors could completely over-shadow the natural variation. I therefore optimized and cross-evaluated two single-molecule mRNA detection methods. Several problems were identified and solutions discussed. I succeeded in building a functional RpoS protein fusion, and used bulk methods to show that the RpoS feedback loop is effectively not operating during exponential- phase growth. Mathematical analyses and initial experiments in a microfluidic device further suggest that the RpoS system has several unusual properties contributing towards extremely fast stress response. A stochastic analysis further suggests that the RpoS feedback loop cannot suppress spontaneous fluctuations, and preliminary experiments indicate that large deviations might indeed play important roles.

The innate immune system is of central importance to the early containment of infection. When receptors of innate immunity recognize molecular patterns on pathogens, they initiate an immediate immune response by inducing the expression of cytokines and other host defense genes. Altered expression or function of the receptors, the molecules that mediate the signal transduction cascade, or the cytokines themselves can predispose individuals to infectious or autoimmune diseases. Here we used genomic approaches to uncover novel components underlying the innate immune response to cytosolic DNA and to characterize variation in the innate immune responses of human dendritic cells to bacterial and viral ligands. In order to identify novel genes involved in the cytosolic DNA sensing pathway, we first identified candidate proteins that interact with known signaling molecules or with dsDNA in the cytoplasm. We then knocked down 809 proteomic, genomic, or domain-based candidates in a high-throughput siRNA screen and measured cytokine production after DNA stimulation. We identified ABCF1 as a critical protein that associates with DNA and the known DNA-sensing components, HMGB2 and IFI16. We also found that CDC37 regulates stability of the signaling molecule, TBK1, and that chemical inhibition of CDC37 as well as of several other pathway regulators (HSP90, PPP6C, PTPN1, and TBK1) potently modulates the innate immune response to DNA and to retroviral infection. These proteins represent potential therapeutics targets for infectious and autoimmune diseases that are associated with the cytosolic DNA response. We also developed a high-throughput functional assay to assess variation in responses of human monocyte-derived dendritic cellsto LPS (receptor: TLR4) or influenza (receptors: RIG-I and TLR3), with the goal to ultimately map genetic variants that influence expression levels of pathogen-responsive genes. We compared the variation in expression between the dendritic cells of 30 different individuals, and within paired samples from 9 of these individuals collected several months later. We found genes that have significant inter- vs. intra-individual ariation in response to the stimuli, suggesting that there is a substantial genetic component underlying variation in these responses. Such variants may help to explain differences between individuals’ risk for infectious, autoimmune, or other inflammatory diseases.

The field of synthetic biology seeks to revolutionize the scope and scale of what is currently feasible by genetic engineering. By focusing on engineering general signal processing platforms using modular genetic parts and devices rather than `one-off' systems, synthetic biologists aim to enable plug-and-play genetic circuits readily adaptable to different contexts. For mammalian systems, the goal of synthetic biology is to create sophisticated research tools and gene therapies. While several isolated parts and devices exist for mammalian systems there are few signal processing platforms available. We addressed this need by creating a transcriptional regulatory framework using programmable zinc finger (ZF) and TALE transcription factors and a conceptual framework for logical T-cell receptor signaling. We first engineered a large set of ZF activator and repressor transcription factors and response promoters. ZFs are scalable elements as they can be engineered to bind to given DNA sequences. We demonstrated that we could ‘tune’ the activity of the ZF transcription factors by fusing them to protein homo-dimerization domains and by modifying their response promoters. We also created OR and NOR logic gates using hybrid promoters and AND and NAND logic gates by reconstituting split zinc finger activators and repressors with split inteins. Next, using a computational algorithm we designed a series of TALE transcriptional activators and repressors predicted to be orthogonal to all 2kb human promoter regions and thus minimally interfere with endogenous gene expression. TALEs can be designed to bind to even longer DNA sequences than ZFs, however off-target binding is predicted to occur. We tested our computationally designed TALEs in human cells demonstrating that they activated their intended target genes, but not their likely endogenous off-target genes, nor synthetic promoters with binding site mismatches. Finally, we created a conceptual framework for logical T-cell-mediated killing of target cells expressing combinations of surface antigens. The systems consist of conventional and novel chimeric antigen receptors (CARs) containing inhibitory or co-stimulatory cytoplasmic signaling domains. In co-incubation assays of engineered T-cells with target cells we demonstrated a functioning OR-Gate system and progress toward development of a functional NOT-Gate system using the CD300a and CD45 inhibitory receptor domains.

Reductionist biology has yielded tremendous insight into the basis of biochemistry and genetic disease. However, the remarkable failure of reductionist biology to explain complex problems, especially cancer, has led to the development of systems biology. The vast complexity of biological systems remains the most difficult problem in biology today. In order to understand this complexity, we need tools to massively multiplex measurements of a signaling network. Therefore, we developed lysate microarray technology to fill this need. In this work, we discuss three ways in which lysate microarrays were applied to human disease. In the first work, we discuss a key stage in malaria development. The liver-stage malaria parasite represents a promising target for intervention, and we present the first use of lysate microarray technology as a screening tool for host-parasite interactions in an infectious disease. We identified three cancer-related pathways that are modified in malaria infection, and studied the p53 pathway in depth. Our finding that the parasite downregulates p53 and that treatment with Nutlin-3 strongly decreases parasite load may lead to the development of a prophylactic malaria vaccine. In the second work, we began by screening drug combinations and varying dosing schedule in triple-negative breast cancers (TNBCs). We systematically explored stimulation space and collected a large lysate microarray dataset, which was used for statistical analysis. We identified a sensitization effect when a growth factor signaling inhibitor was presented before a genotoxic agent. This sensitization was generalizable among a subset of TNBCs and may generally be important for cancers driven by growth factor signaling, as we found the effect extends to nonTNBC cancers. We hope this data will be useful in guiding cancer treatment strategies in patients. In the third work, we study the changing role of the DNA Damage Response (DDR) as a cell line evolves towards cancer. We used the MCF10A progression series and studied how these cell lines respond to genotoxic agents. We identified differences in cell fates after treatment, and collected a large lysate microarray dataset for statistical analysis. Early analysis of the data indicates gross rewiring within the DDR between the MCF10A cell lines.

Regulation of gene expression is essential for many biological processes. Binding of transcription factors to DNA is a key regulatory step in the control of gene expression. It is commonly observed that DNA sequences with high affinity for transcription factors occur more frequently in the genome than the instances of genes bound or regulated by these factors. However, the mechanism by which transcription factors selectively identify and regulate these genes was unclear. I utilized the transcriptional control of the phosphate-responsive signaling pathway (PHO) in Saccharomyces cerevisiae as a model system to address this problem.

This thesis is composed of two problems. The first is a systems level analysis of the carbon concentrating mechanism in cyanobacteria. The second presents a theoretical analysis of femtosecond laser melting for the purpose of hyperdoping silicon with sulfur. While these systems are very distant, they are both relevant to the development of alternative energy (production of biofuels and methods for fabricating photovoltaics respectively). Both problems are approached through analysis of the underlying diffusion equations.

Patterning, morphogenesis, and cell divisions are distinct processes during development yet are concurrent and likely highly integrated. However, it has been challenging to investigate them as a whole. Recent advances in imaging and labeling tools make it possible to observe live tissues with high coverage and resolution. In this dissertation work, we developed a novel imaging platform that allowed us to fully capture the early neural tube formation process in live zebrafish embryos at cellular resolution. Importantly, these datasets allow us to reliably track single neural progenitors. These tracks carry information on the history of cell movement, shape change, division, and gene expression all together. By comparing tracks of different progenitor fates, we found they show a spatially noisy response to Sonic hedgehog (Shh) and become specified in a positionally mixed manner, in surprising contrast to the "French Flag" morphogen patterning model. Both cell movement and division contribute to cell mixing. In addition, we decoupled the temporal and genetic regulatory network (GRN) noises in Shh interpretation using tracks that carry both Shh signaling and cell fate reporters. Our tracks suggest that, after specification, progenitors undergo sorting to self-assemble a sharp pattern. Consistent with this hypothesis, we found ectopically induced progenitors move to correct locations. Furthermore, we show that proper adhesion is required for cell sorting to happen (Chapters 2 and 3). In the cleavage stage embryos, the cells on the surface undergo shape changes followed by lineage separation and differentiation. We quantitatively measured this morphogenesis process and tracked cell divisions. By applying a mathematical model we uncover a predictive, and perhaps general link between cell division orientation, mechanical interaction, and the morphogenetic behavior of the whole surface layer (Chapter 4). Finally, we discuss the concepts and tools of cell tracking including a multi-color cell labeling method we developed by modifying the "Brainbow" system (Chapter 5). Together this dissertation showcases the importance and promise of live observation based, quantitative and integrated analysis in our understanding of complex multi-cellular developmental processes.

Genetic variation has a powerful impact on human metabolism and disease. Traditionally, this relationship has either been studied at a high level using top-down descriptive studies of patients with genetically defined inborn errors of metabolism, or else from the bottom up, with molecular biology and biochemical studies of single proteins. Recent advances in genetic sequencing, metabolic profiling technology, and structural biology are rapidly enabling the integration of these approaches towards a more complete description of human metabolism.