The Shroom family of proteins is currently comprised of four members, Shroom1, 2, 3 and 4. Since Shroom3 was shown to be a critical protein for neural tube closure, the other three proteins are also expected to play an important role for proper development. However, their functions during development were not clear. To address this, my study started with Shroom3 function in the neural plate. Shroom3 had been previously known to induce apical constriction by controlling actin filaments in neuroepithelial cells. My studies show that Shroom3 induces apico-basal cell heightening by controlling parallel microtubule assembly. Shroom3 is able to change the distribution of γ-tubulin, suggesting that Shroom3 controls apical constriction and apico-basal cell elongation via both actin filaments and microtubules. The ability to control γ-tubulin distribution is possessed not only by Shroom3, but also by all other Shroom proteins, although they can not induce apical constriction. In addition, they are expressed in tissues which contain apico-basally elongated cells. Data from functional assays with Shroom2 show that it induces cell elongation and is required for proper cell shape in deep layer neuroepithelial cells in Xenopus. These data suggest that Shroom family proteins control cell architecture during morphogenetic development. I have discovered another role for Shroom2. By comparative analysis with Xenopus and Physalaemus, which have different pigment patterns in eggs, I show that a high level of maternal Shroom2 mRNA is important for pigment polarity in Xenopus. Furthermore, Shroom2 controls the distribution of spectrin which plays a role in pigment granule movement. Thus, Shroom2 is suggested to be a key molecule to control the pigment polarity in amphibian eggs. Together all these data suggest that Shroom family proteins play a role in cell morphogenesis and polarization via controlling the cytoskeleton during Xenopus development. / text

Many physical systems break symmetry in their evolution. Biophysical systems, such as cells, developing organisms, and even entire populations, are no exception. Developing neurons represent a striking example of a biophysical system that breaks symmetry: neurons cultured in vitro begin as cell bodies with several tendrils (“neurites”) growing outward. A few days later, these same neurons invariably have the same new morphology: exactly one of the neurites (the “axon”) has grown hundreds of microns in length, while the others (the “dendrites”) are much shorter and are more branched. Previous work has shown that any of the neurites can become the axon, and so neurons must break symmetry during their development. The mechanisms underlying neuronal symmetry breaking and axon specification have recently attracted attention, with multiple groups proposing biophysical models to explain the phenomena. In this thesis, we perform the first analytical comparisons of these models by conducting multiple phenotypic and morphological studies of neurite growth in developing neurons. Studying neurite dynamics is technically challenging because neurites have unpredictable morphologies. In Chapter 4, we study neurite competition and neuronal symmetry breaking in hundreds of neurons by optically patterning micron-wide stripes to which the neurons adhere, and on which they grow exactly two neurites. We then use our measurements to test the accuracy of the models in the simple case when a neuron has exactly two neurites. In Chapter 5, we no longer constrain neuronal morphology. One characteristic of symmetry breaking systems is how the system’s complexity affects the symmetry breaking. We find that a majority of the models predict that neurons with more neurites break symmetry much slower than neurons with fewer neurites. Experimentally, we find that neurons with different neurite counts break symmetry at the same rate, consistent with previous observations. We then determine why the models disagree in their predictions, and rectify the models using our own experimental data. In particular, we find that neurons with higher neurite counts have higher concentrations of key proteins involved in symmetry breaking, so that neurons, regardless of neurite count, can break symmetry at the same rate. / Physics

In this thesis, I focus on scalar implicatures, presuppositions and their connections. In chapter 2, I propose a scalar implicature-based account of neg-raising inferences, standardly analyzed as a presuppositional phenomenon (Gajewski 2005, 2007). I show that an approach based on scalar implicatures can straightforwardly account for the differences and similarities between neg-raising predicates and presuppositional triggers. In chapters 3 and 4, I extend this account to “soft” presuppositions, a class of presuppositions that are easily suspendable (Abusch 2002, 2010). I show how such account can explain the differences and similarities between this class of presuppositions and other presuppositions on the one hand, and scalar implicatures on the other. Furthermore, I discuss various consequences that it has with respect to the behavior of soft presuppositions in quantificational sentences, their interactions with scalar implicatures, and their effects on the licensing of negative polarity items. In chapter 5, I show that by looking at the interaction between presuppositions and scalar implicatures we can solve a notorious problem which arises with conditional sentences like (1) (Soames 1982, Karttunen and Peters 1979). The main issue with (1) is that it is intuitively not presuppositional and this is not predicted by any major theory of presupposition projection. (1) I’ll go, if you go too. Finally, I explore in more detail the question of which alternatives should we consider in the computation of scalar implicatures (chapter 6). Traditionally, the answer has been to consider the subset of logically stronger alternatives than the assertion. Recently, however, arguments have been put forward in the literature for including also logically independent alternatives. I support this move by presenting some novel arguments in its favor and I show that while allowing new alternatives makes the right predictions in various cases, it also causes an under- and an over-generation problem. I propose a solution to each problem, based on a novel recursive algorithm for checking which alternatives are to be considered in the computation of scalar implicatures and the role of focus (Rooth 1992, Fox and Katzir 2011). / Linguistics

The ability to spatially restrict specific activities across the cell cortex functionally defines individual cells and tissues. This is achieved, in part, via the assembly of protein complexes that link the plasma membrane to the underlying cortical actin cytoskeleton. The neurofibromatosis type 2 (NF2) tumor suppressor Merlin and closely related ERM proteins (Ezrin, Radixin and Moesin) are a special class of such membrane:cytoskeleton associated proteins that function to organize specialized cortical domains. In addition to their high degree of similarity, mounting evidence suggests that Merlin/ERMs share a functional relationship, which is largely unexplored. Unlike Merlin, the ERMs are not known to inhibit cell proliferation; in fact, Ezrin is thought to promote tumor metastasis. Defining the relationship between Merlin and the ERMs is essential to appreciating their respective roles in cancer development. Here I demonstrate a novel role for Merlin and the ERMs in generating cortical asymmetry in the absence of external cues. Our data reveal that Merlin functions to restrict the cortical distribution of Ezrin, which in turn positions the interphase centrosome in single epithelial cells and 3D organotypic cultures. In the absence of Merlin, ectopic cortical Ezrin yields mispositioned centrosomes, misoriented spindles and aberrant epithelial architecture. Furthermore, in tumor cells with centrosome amplification, the failure to restrict cortical Ezrin abolishes centrosome clustering, yielding multipolar mitoses. Consistent with a functional relationship, I observe a strong genetic interaction between Nf2 and Ezrin in the mouse intestine in vivo. Finally, I begin to address the basis of their functional interaction by testing whether they are coordinately regulated by the Ste-20 like kinase SLK. Altogether, these data uncover fundamental roles for Merlin/ERM proteins in spatiotemporally organizing the cell cortex in vitro and in vivo and suggest that Merlin’s role in promoting cortical heterogeneity may contribute to tumorigenesis by disrupting cell polarity, spindle orientation and potentially genome stability.

Mathematical modeling has been important in the study of biology. Two main challenges with modeling biological problems are the lack of quantitative data and the complexity of biological problems. With the invention of new techniques, like single molecule transcript counting, very quantitative gene expression measurements at the level of single transcript in individual cells can now be obtained. Biological systems are very complex, involving many reactions and players with unknown reaction rates. To reduce the complexity, scientists have often proposed simplified phenomenological models that are tractable and capture the main essence of the biological systems. These simplified models allow scientists to describe the behavior of biological systems with a few meaningful parameters. In this thesis, by integrating quantitative single-cell measurements with phenomenological modeling, we study the (1) roles of Wnt ligands and receptors in sensing and amplification in Caenorhabditis elegans’ P cells and (2) regulation of rDNA transcription in Saccharomyces cerevisiae. The initiation of cell polarity consists of two sequential processes: an external gradient is first sensed and then the resulting signal is amplified by intracellular signaling. It is challenging to determine the role of proteins towards sensing and amplification as these two processes are intertwined. We integrated quantitative single-cell measurements with phenomenological modeling to determine the roles of Wnt ligands and receptors in sensing and amplification in the P cells of Caenorhabditis elegans. By systematically exploring how P cell polarity is altered in Wnt ligand and receptor mutants, we inferred that ligands predominantly affect sensing, whereas receptors are needed for both sensing and amplification. Most eukaryotes contain many tandem repeats of ribosomal RNA genes of which only a subset is transcribed at any given time. Current biochemical methods allow for the determination of the fraction of transcribing repeats (ON) versus nontranscribing repeats (OFF) but do not provide any dynamical information. By using the single molecule transcript counting technique complemented with theoretical modeling, we determine the rate of switching from OFF to ON (activation rate) and the average number of RNA molecules produced during each transcriptional burst (burst size). We explore how these two variables change in mutants and different growth conditions.

The relationship between MUC1 and EGFR has been characterized by our lab to be highly tumorigenic. A peptide therapeutic was developed in our lab to block the cytoplasmic interaction of MUC1 and EGFR by competing with the EGFR-binding domain of MUC1. The peptide, PMIP, reduced invasion and proliferation in vitro and reduced tumor growth and metastasis in vivo. These studies demonstrated the potency of MUC1/EGFR interactions in tumor progression, and we sought to explore this concept further. We wanted to clarify a mechanism by which MUC1 and EGFR together drive breast cancer metastasis, and we identified c-Met as a mediator of MUC1 and EGFR-driven cell motility. In two separate assays, we demonstrated that c-Met activity was necessary for MUC1 and EGFR to promote migration and invasion. In addition, we wanted to identify the role of EGFR membrane localization in membrane identity and tumor initiation. We established several EGFR localization mutants to compare to wild-type basolateral EGFR and we performed proof-of-concept experiments to show that these mutants will be useful in future studies. Finally, we studied the effect of MUC1 and EGF loss on tissue architecture and function in the lactating mammary gland. EGF is the primary ligand for EGFR during lactation, and MUC1 is highly expressed during this period of mammary development. In addition, it has been shown that EGFR and MUC1 interact at the apical cell surface of lactating mammary ducts, yet there is no link between lactation and tumor formation. We hypothesized that MUC1 and EGFR interaction may have a role in maintaining tissue architecture and lactation function in the mouse mammary gland. We found instead that the loss of MUC1 and EGF had no noticeable effect on lactation and did not result in tissue defects. These studies further clarified the relationship between MUC1 and EGFR in several different contexts, showing a role for their interaction in metastatic progression, and showing that their ablation has no effect in the lactating mammary gland. Future studies will elucidate the role of MUC1 and EGFR interaction in tumor initiation, and we have taken several steps in our studies toward that goal.

In this dissertation I develop a theory that seeks to account for the variation in stability and conflict proneness we observe across regions. I propose that the observed variation in regional order in the international system is fundamentally rooted in the polar arrangements of the different regions. Specifically, I argue that regions that do not have clearly recognized regional powers are more prone to conflict, that their conflicts are more severe, and that these regions are more vulnerable to outside influence than those that do have such powers. Using an opportunity and willingness framework, I define regions as stable geographic spaces of interacting states behaving uniquely from the broader international system. In order to test these propositions, I make use of novel data defining both regional memberships and that identifies leading regional actors. The results show that not only do regional polarity have a strong explanatory effect, but they also suggest that it is necessary to take regional-level effects into account when analyzing international politics.

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No description available.

During development, cells consume energy, divide, rearrange, and die. Bulk properties such as viscosity and elasticity emerge from cell-scale mechanics and dynamics. Order appears, for example in patterns of hair outgrowth, or in the predominately hexagonal pattern of cell boundaries in the wing of a fruit fly. In the past fifty years, much progress has been made in understanding tissues as living materials. However, the physical mechanisms underlying tissue-scale behaviour are not completely understood. Here we apply theories from statistical physics and fluid dynamics to understand mechanics and order in two-dimensional tissues. We restrict our attention to the mechanics and dynamics of cell boundaries and vertices, and to planar polarity, a type of long-ranged order visible in anisotropic patterns of proteins and hair outgrowth. Our principle tool for understanding mechanics and dynamics is a vertex model where cell shapes are represented using polygons. We analytically derive the ground-state diagram of this vertex model, finding it to be dominated by the geometric requirement that cells be polygons, and the topological requirement that those polygons tile the plane. We present a simplified algorithm for cell division and growth, and furthermore derive a dynamic equation for the vertex model, which we use to demonstrate the emergence of quasistatic behaviour in the limit of slow growth. All our results relating to the vertex model are consistent with and build off past calculations and experiments. To investigate the emergence of planar polarity, we develop quantification methods for cell flow and planar polarity based on confocal microscope images of developing fly wings. We analyze cell flow using a velocity gradient tensor, which is uniquely decomposed into terms corresponding to local compression, shear, and rotations. We argue that a pattern in an inhomogeneously flowing tissue will necessarily be reorganized, motivating a hydrodynamic theory of polarity reorientation. Using such a coarse-grained theory of polarity reorientation, we show that the quantified patterns of shear and rotation in the wing are consistent with the observed polarity reorganization, and conclude that cell flow reorients planar polarity in the wing of the fruit fly. Finally, we present a cell-scale model of planar polarity based on the vertex model, unifying the themes of this thesis.