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The confluence of next generation DNA sequencing and synthesis when combined with the application of concepts such as standardization and modular design has led to the genesis of a new discipline. The nascent field of Synthetic Biology concerns the rational design and construction of genetic circuits, pathways, machines and eventually whole organisms. The immaturity of this field dictates that early research efforts, including this Thesis, describe foundational work towards the creation of tools which make biology more amenable to being engineered. The first part of this Thesis describes an attempt to standardize the measurement of transcriptional promoter activity in E. coli. A method to measure in vivo promoter activity was developed for E. coli and tested in a multi-institution trial. Comparable results were achieved with less than a two-fold range for the measured promoters across eight laboratories. A standardized measurement kit was created and distributed for use by the teams participating in the 2008 international Genetically Engineered Machines competition. Techniques learned measuring the activity of E. coli promoters were applied to a collection of S. cerevisiae strains. Several promoters were measured in synthetic dextrose media and ADH1 was measured in multiple media conditions. The outcome of these experiments is to consider proposing ADH1as the reference promoter in S. cerevisiae. The second aspect of this Thesis describes the construction of artificial organelles in S. cerevisiae. Artificial organelles hold the prospect of being able to insulate synthetic genetic pathways from the cell. Two proteins are essential for the biogenesis of the peroxisome organelle in humans and yeast, Pex3p and Pex19p. Pex3p functions as a peroxisomal membrane receptor for Pex19p, while Pex19p shuttles other peroxisomal proteins to the membrane, including Pex3p, creating a feedback loop. Human Pex19p has previously been shown to dock to yeast Pex3p and a version of yeast Pex19p has been shown to work with human Pex3p as a high degree of evolutionary conservation exists between these proteins. Because of these inter-species protein docking characteristics, there exists the possibility of creating bimodality: the ambition of the work was therefore to create a cell strain which possessed both synthetic “humanized” and natural yeast peroxisomes. An S. cerevisiae BY4741a derivative strain was engineered with fluorophore tagged versions of human (CFP) and yeast (YFP) Pex3p and untagged yeast and human Pex19p proteins. The results indicated the creation of a single population of peroxisomes when a measure of fluorescently imaged CFP and YFP peroxisomes were plotted on a scatter plot. A log of the ratio of CFP to YFP peroxisomes was plotted on a histogram and a normal distribution was found to best fit the curve, indicating a lack of bimodality. Finally, microscopy images of this strain were reviewed and by visual inspection, showed no evidence of distinct human or yeast peroxisomes. This experiment therefore produced no evidence of bimodality when examining the interactions of human and yeast Pex3p and Pex19p proteins. However, the four proteins were shown to interact closely to produce a single population of chimeric human-yeast peroxisomes. The peroxisome-deficient mutant phonotype strain was rescued using human Pex3p and Pex19p.

The enzymatic deconstruction of lignocellulosic plant biomass is performed by specialist microbial species. It is a ubiquitous process within nature and central to the global recycling of carbon and energy. Lignocellulose is a complex heteropolymer, highly recalcitrant and resistant to hydrolysis due to the major polysaccharide cellulose existing as a crystalline lattice, intimately associated with a disordered sheath of hemicellulosic polysaccharides and lignin. In this thesis I aim to transfer the highly efficient cellulolytic mechanism of the bacterium Cellulomonas fimi, to that of a suitably amenable and genetically tractable expression host, in the hopes of better understanding the enzymatic hydrolysis of lignocellulose. Using tools and concepts from molecular biology and synthetic biology, I constructed a library of standardised genetic parts derived from C. fimi, each encoding a known enzymatic activity involved in the hydrolysis of cellulose, mannan or xylan; three of the major polysaccharides present in lignocellulose. Characterization assays were performed on individual parts to confirm enzymatic activity and compare efficiencies against a range of substrates. Results then informed the rational design and construction of parts into modular devices. The resultant genetic devices were introduced into the expression hosts Escherichia coli and Citrobacter freundii, and transformed strains were assayed for the ability to utilize various forms of xylan, mannan and cellulose as a sole carbon source. Results identified devices which when expressed by either host showed growth on the respective carbon sources. Notably, devices with improved activity against amorphous cellulose, crystalline cellulose, mannan and xylan were determined. Recombinant cellulase expressing strains of E. coli and C. freundii were shown capable of both deconstruction and utilization of pure cellulose paper as a sole carbon source. Moreover, this capacity was shown to be entirely unhindered when C. freundii strains were cultured in saline media. These findings show promise in developing C. freundii for bioprocessing of biomass in sea water, so as to reduce the use of fresh water resources and improve sustainability as well as process economics. Work presented in this thesis contributes towards understanding the complementarities and synergies of the enzymes responsible for lignocellulose hydrolysis. Moreover, the research emphasizes the merits of standardizing genetic parts used within metabolic engineering projects and how adopting such design principles can expedite the research process.

<p>This thesis develops Bayesian latent class models for nested categorical data, e.g., people nested in households. The applications focus on generating synthetic microdata for public release and imputing missing data for household surveys, such as the 2010 U.S. Decennial Census.</p><p>The first contribution is methods for evaluating disclosure risks in fully synthetic categorical data. I quantify disclosure risks by computing Bayesian posterior probabilities that intruders can learn confidential values given the released data and assumptions about their prior knowledge. I demonstrate the methodology on a subset of data from the American Community Survey (ACS). The methods can be adapted to synthesizers for nested data, as demonstrated in later chapters of the thesis.</p><p>The second contribution is a novel two-level latent class model for nested categorical data. Here, I assume that all configurations of groups and units are theoretically possible. I use a nested Dirichlet Process prior distribution for the class membership probabilities. The nested structure facilitates simultaneous modeling of variables at both group and unit levels. I illustrate the modeling by generating synthetic data and imputing missing data for a subset of data from the 2012 ACS household data. I show that the model can capture within group relationships more effectively than standard one-level latent class models.</p><p>The third contribution is a version of the nested latent class model adapted for theoretically impossible combinations, e.g. a household with two household heads or a child older than her biological father. This version assigns zero probability to those impossible groups and units. I present a proof that the Markov Chain Monte Carlo (MCMC) sampling strategy estimates the desired target distribution. I illustrate this model by generating synthetic data and imputing missing data for a subset of data from the 2011 ACS household data. The results indicate that this version can estimate the joint distribution more effectively than the previous version.</p> / Dissertation

Underwater acoustic modelling is an important aspect of Synthetic Aperture Sonar (SAS) system design and algorithm development. Sea-trials are an expensive and time-consuming exercise and simulations provide an efficient and economic alternative. However, there are few simulators (in the open literature) that can efficiently provide realistic SAS data for large, complicated scenes. Conventional side-scan sonar simulators are not suitable for SAS data simulation. These simulators utilise narrow-beam and narrow-band approximations; typical SAS systems are wide-beam and wide-band and these approximations are invalid. Moreover, conventional side-scan sonar is a non-coherent imaging technique and SAS processing relies on the phase. Existing SAS simulators are capable of modelling very simple scenes only. They utilise a decomposition of the scene into point or smooth facet primitives, which is very inefficient. Many primitives are required and this imposes a severe restriction on scene complexity and size. This thesis presents a rigorous mathematical framework for the modelling of SAS imagery. A novel acoustic scattering model is developed and its implementation in a wide-beam and wide-band, multiple-receiver Interferometric SAS (InSAS) simulator is detailed. The scattering model utilises a decomposition of the scene into rough (rather than smooth) facet primitives. The use of rough facet primitives provides a significant increase in computational efficiency since scenes are decomposed into fewer primitives. This facilitates the simulation of larger and more complicated scenes. Each rough facet is characterised by its far-field beampattern. The statistics of the beampattern are related to the facet shape and roughness statistics using the Kirchhoff approximation. The beampattern is realised from its first and second-order statistics. The SAS imagery is obtained using a coherent sum of the facet responses and occlusions and multiple-scattering are resolved by ray-tracing. The simulator is implemented for use on a parallel computing cluster. The simulator is shown to provide realistic SAS data that is qualitatively and quantitatively similar to real data. The simulated results are considered, in many ways, superior to the simulated results in the literature.