Transcription Factor Engineering: Tools and Applications

Transcription factors play a vital role in the biology of every organism. By controlling gene expression they regulate growth, development, metabolism, reproduction, signaling, and response to the environment. They have also provided the basis for many useful tools in molecular biology. The estrogen receptor alpha is one of the most studied human transcription factors and acts as a ligand controlled regulator of transcription. The modular design of this and other transcription factors allows for the rational design of artificial gene switches to control expression of desired genes. In this thesis I explore some tools for, and applications of, engineering the estrogen receptor. Beginning with two ligand binding domain mutants previously engineered to recognize the small molecules 4,4???-dihydroxybenzil (DHB) or 2,4-di(4-hydroxyphenyl)-5-ethylthiazole (L9), I showed that they could be used as a gene switch to independently control reporter genes in yeast and mammalian cells. By using different DNA binding domains, activation and repression domains, promoter elements, and a luciferase reporter I implemented the logic functions AND, OR, NAND, and NOR in HeLa cell culture. My research revealed some of the limitations of both the modular engineering approach, and the yeast two-hybrid screening assay used to engineer the ligand binding domain. I explored the feasibility of performing directed evolution of gene switches in mammalian cells through a protoplast fusion method, which combines the benefits of simple library creation with screening in a functionally relevant system. Although individual steps of the process were successful, the method proved unsuitable for large scale screening of libraries. The endogenous gene vascular endothelial growth factor-A (VEGF-A) was targeted for control by a gene switch. The effect of construct design was evaluated using a VEGF-A promoter controlled luciferase gene and performance was impacted by the choice of DNA binding domain, activation domain, and the order of domain use. Endogenous VEGF-A protein secretion in HeLa cells was successfully upregulated twofold by a DHB ligand controlled gene switch. Finally, I developed a useful biosensor for estrogenic compound detection that has the advantage of requiring no added substrates for signal generation. Through fusing the N and C terminal halves of the fluorescent protein Venus to the receptor ligand binding domain, fluorescence complementation generated a robust signal upon addition of an estrogenic ligand. The biosensor was capable of responding to a range of endogenous, pharmaceutical, environmental, and industrial compounds with sensitivities that correlated with their relative binding affinity. The signal characteristics were seen to depend on the length of the LBD region used, with some constructs distinguishing between agonists and antagonistic ligands

Do unbalanced data have a negative effect on LDA?

For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class) unbalanced data set had a negative effect on the performance of linear discriminant analysis (LDA). Through re-balancing 10 real-world data sets, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] provided empirical evidence to support the claim using AUC (Area Under the receiver operating characteristic Curve) as the performance metric. We suggest that such a claim is vague if not misleading, there is no solid theoretical analysis presented in Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562], and AUC can lead to a quite different conclusion from that led to by misclassification error rate (ER) on the discrimination performance of LDA for unbalanced data sets. Our empirical and simulation studies suggest that, for LDA, the increase of the median of AUC (and thus the improvement of performance of LDA) from re-balancing is relatively small, while, in contrast, the increase of the median of ER (and thus the decline in performance of LDA) from re-balancing is relatively large. Therefore, from our study, there is no reliable empirical evidence to support the claim that a (class) unbalanced data set has a negative effect on the performance of LDA. In addition, re-balancing affects the performance of LDA for data sets with either equal or unequal covariance matrices, indicating that having unequal covariance matrices is not a key reason for the difference in performance between original and re-balanced data

Increasing the Environmental Relevance of Biodegradation Testing by Focusing on Initial Biodegradation Kinetics and Employing Low-Level Spiking

The environmental relevance of standard biodegradation tests such as OECD 309 has been questioned. Challenges include the interpretation of changing degradation kinetics over the 60–90 incubation days and the effects of chemical spiking on the microbial community. To ameliorate these weaknesses, we evaluated a modified OECD 309 test using water and sediment from three Swedish rivers. For each river, we had three treatments (no spiking, 0.5 μg L–1 spiking, and 5 μg L–1 spiking). The dissipation of a mixture of 56–80 spiked chemicals was followed over 14 days. Changes in dissipation kinetics during the incubation were interpreted as a departure of the microbial community from its initial (natural) state. The biodegradation kinetics were first-order throughout the incubation in the no spiking and 0.5 μg L–1 spiking treatments for almost all chemicals, but for the 5 μg L–1 treatment, more chemicals showed changes in kinetics. The rate constants in the no spiking and 0.5 μg L–1 treatments agreed within a factor of 2 for 35 of 37 cases. We conclude that the environmental relevance of OECD 309 is improved by considering only the initial biodegradation phase and that it is not compromised by spiking multiple chemicals at 0.5 μg L–1. KEYWORDS: biodegradation river water sediment micropollutants OECD 30

High-throughput evaluation of organic contaminant removal efficiency in a wastewater treatment plant using direct injection UHPLC-Orbitrap-MS/MS

Removal efficiency can be estimated from non-target data using the ratio of peak areas in effluent and influent

Understanding Indigenous Food Sovereignty through an Indigenous Research Paradigm

The Indigenous food sovereignty (IFS) movement offers insight into food-related challenges that confront Indigenous Peoples in Canada. The philosophy of IFS is holistic in nature and sees food as encompassing all facets of being – the mental, emotional, spiritual, and intellectual. Thirty-two interviews were conducted across western Canada to better understand Indigenous food sovereignty practices. Indigenous research methodologies offer further insight into IFS studies, in part, through an epistemology centered on experiential knowledge, relational accountability, respect, and reciprocity. The values of these methodologies are reflected in this research regarding IFS, and provide an important and appropriate context for this work. In particular, metaphor, as a research tool, helps to further the understanding of IFS by acknowledging the harmony that can and should exist between food and nature

Playing Guns: Avant-Garde Aesthetics and Revolutionary Violence

Playing Guns theorizes the avant-gardes in relation to the following revolutionary movements from the extended Caribbean: the Mexican Revolution (Stridentism and Antonio Helú), the Cuban Revolution (Julio Cortázar), the Sandinista Revolution (Gioconda Belli), and post-NAFTA Mexico (Roberto Bolaño, Subcomandante Marcos and Paco Ignacio Taibo II). These examples, in turn, help elucidate the following theoretical-historical problems: the Caribbean and Latin America as privileged sites of revolt and revolution; human emancipation in relation to interpellation and agency; and practices of confrontation vis-à-vis practices of resistance. I argue that Latin American avant-garde artists, movements and institutions engage in a radical variant of what Rancière theorizes as aesthetic free play—an egalitarian rearranging of our common sensorium that overturns social hierarchies. By doing so, the avant-gardes “recognize,” in Althusserian terms, the actual interpenetration of life and art and thereby call into question certain caricatures of the avant-gardes as counterrevolutionary and politically vacuous. I then propose that free play propagates radical modes of being that can lead to forms of human emancipation as they confront—not resist as Foucault theorizes—interpellating hierarchies from peripheral positions proper to Latin America. William Egginton and Eduardo González served as advisors for this dissertation

Learning Mixtures of Gaussians in High Dimensions

Efficiently learning mixture of Gaussians is a fundamental problem in statistics and learning theory. Given samples coming from a random one out of k Gaussian distributions in Rn, the learning problem asks to estimate the means and the covariance matrices of these Gaussians. This learning problem arises in many areas ranging from the natural sciences to the social sciences, and has also found many machine learning applications. Unfortunately, learning mixture of Gaussians is an information theoretically hard problem: in order to learn the parameters up to a reasonable accuracy, the number of samples required is exponential in the number of Gaussian components in the worst case. In this work, we show that provided we are in high enough dimensions, the class of Gaussian mixtures is learnable in its most general form under a smoothed analysis framework, where the parameters are randomly perturbed from an adversarial starting point. In particular, given samples from a mixture of Gaussians with randomly perturbed parameters, when n > {\Omega}(k^2), we give an algorithm that learns the parameters with polynomial running time and using polynomial number of samples. The central algorithmic ideas consist of new ways to decompose the moment tensor of the Gaussian mixture by exploiting its structural properties. The symmetries of this tensor are derived from the combinatorial structure of higher order moments of Gaussian distributions (sometimes referred to as Isserlis' theorem or Wick's theorem). We also develop new tools for bounding smallest singular values of structured random matrices, which could be useful in other smoothed analysis settings

Sandy beach social–ecological systems at risk: regime shifts, collapses, and governance challenges

Approximately half of the world’s ice-free ocean coastline is composed of sandy beaches, which support a higher level of recreational use than any other ecosystem. However, the contribution of sandy beaches to societal welfare is under increasing risk from local and non-local pressures, including expanding human development and climate-related stressors. These pressures are impairing the capacity of beaches to meet recreational demand, provide food, protect livelihoods, and maintain biodiversity and water quality. This will increase the likelihood of social–ecological collapses and regime shifts, such that beaches will sustain neither the original ecosystem function nor the related services and societal goods and benefits that they provide. These social–ecological systems at the land–sea interface are subject to market forces, weak governance institutions, and societal indifference: most people want a beach, but few recognize it as an ecosystem at risk.CSIC: Grupos ID 3