Cell surface $\beta$-1,4-galactosyltransferase function during invasion and metastasis

Metastasis is the complex process of tumor cell spread which is responsible for the majority of cancer-related deaths. Metastasis necessitates complex phenotypic changes, many of which are mediated by changes in the activities of cell surface molecules. One of these is cell surface $\beta$1,4-galactosyltransferase (GalTase), which is elevated on more highly metastatic cells. In this study, both molecular and biochemical methods were used to perturb and manipulate cell surface GalTase levels on K1735 murine melanoma cell lines in order to examine its function in metastasis.^ As expected, highly metastatic K1735 variants have higher cell surface GalTase than poorly metastatic variants. Stably transfected K1735 cell lines that overexpress surface GalTase were created. These cell lines were assayed for metastatic ability using an invasion chamber with Matrigel-coated filter inserts. Cells with increased surface GalTase were uniformly more invasive than neo transfected controls. With multiple cell lines, there was a direct correlation (r = 0.918) between surface GalTase activity and invasiveness. Homologous recombination was used to create K1735 cells with decreased levels of surface GalTase. These cells were uniformly less invasive than controls. Cell surface GalTase was inhibited using two different biochemical strategies. In both cases, inhibition of surface GalTase led to a decrease in in vivo metastatic ability of K1735 cells. This is the first direct experimental evidence addressing GalTase function in metastasis. These data provide several lines of independent evidence which show that cell surface GalTase facilitates invasion and metastasis. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Middle managers' attitudes toward employee assistance programs in the corporate setting

Several studies have shown that successful Employee Assistance Programs (EAPs) have strong management endorsement. Strong management endorsement is defined as positive support in utilizing EAP services for themselves and their employees. This study focuses solely on middle management as opposed to upper or general management support. The study further examines success or lack of success of an EAP by the utilization rate defined as the number of employees over a year period who access EAP services.^ A analytical cross-sectional design was used to compare and observe differences between two groups of middle managers (utilizers and nonutilizers). Middle manager data was collected through a mail questionnaire. The study focused on identifying predictors that influence middle managers' utilization rate specifically: attitude toward EAPs, EAP knowledge level, attitude toward mental health professionals, age, gender, years worked as a middle manager, education level, training, and other possible predictors of utilization. The overall hypothesis states middle manager utilizers of EAP services have more positive attitudes and a better understanding of their EAP than middle management nonutilizers.^ As predicted, nonparametric bivariate results showed significant differences between the two groups. Middle managers in the utilization group (n = 473) tended to show more positive attitudes toward their EAP and mental health professionals and demonstrated greater EAP knowledge compared to the nonutilization group (n = 154). These findings support past studies on variables that influence EAP utilization rates.^ Further variables found to influence middle management utilization were identified by multivariate logistic regression results. These variable were gender (female supervisors), educational levels of employees supervised (employees with lower levels of education), number of employees supervised (greater the number supervised, more likely to utilize), managerial EAP training (trained supervisors) and awareness that problems do influence an employee's productivity.^ These findings strengthen the assertion that middle management's attitudes, as well as other variables may influence utilization. Study findings add new information about important variables specifically influencing middle management who utilize EAPs. An understanding of these variables is essential in developing competent EAP program training and orientation programs for middle managers. ^

Phototaxis signaling by the membrane complex of archaeal sensory rhodopsins and their transducers

Sensory rhodopsins I and II (SRI and SRII) are visual pigment-like phototaxis receptors in the archaeon Halobacterium salinarum. The receptor proteins each consist of a single polypeptide that folds into 7 $\alpha$-helical membrane-spanning segments forming an internal pocket where the chromophore retinal is bound. They transmit signals to their tightly bound transducer proteins, HtrI and HtrII, respectively, which in turn control a phosphotransfer pathway modulating the flagellar motors. SRI-HtrI mediates attractant responses to orange-light and repellent responses to UV light, while SRII-HtrII mediates repellent response to blue light. Experiments were designed to analyze the molecular processes in the SR-Htr complexes responsible for receptor activation, which previously had been shown by our laboratory to involve proton transfer reactions of the retinylidene Schiff base in the photoactive site, transfer of signals from receptor to transducer, and signaling specificity by the receptor-transducer complex.^ Site-directed mutagenesis and laser-flash kinetic spectroscopy revealed that His-166 in SRI (i) plays a role in the proton transfers both to and from the Schiffbase, either as a structurally critical residue or possibly as a direct participant, (ii) is involved in the modulation of SIU photoreaction kinetics by HtrI, and (iii) modulates the pKa of Asp-76, an important residue in the photoactive site, through a long-distance electrostatic interaction. Computerized cell tracking and motion analysis demonstrated that (iv) His-166 is crucial in phototaxis signaling: a spectrum of substitutions either eliminate signaling or greatly perturb the activation process that produces attractant and repellent signaling states of the receptor.^ The signaling states of SRI are communicated to HtrI, whose oligomeric structure and conformational changes were investigated by engineered sulfhydryl probes. It was found that signaling by the SRI-HtrI complex involves reversible conformational changes within a preexisting HtrI dimer, which is likely accomplished through a slight winding or unwinding of the two HtrT monomers via their loose coiled coil association. To elucidate which domains of the Htr dimers confer specificity for interaction with SRI or SRII, chimeras of HtrI and HtrII were constructed. The only determinant needed for functional and specific interaction with SRI or SRII was found to be the four transmembrane segments of the HtrI or HtrII dimers, respectively. The entire cytoplasmic parts of HtrI and HtrII, which include the functionally important signaling and adaptation domains, were interchangeable.^ These observations support a model in which SRI and SRII undergo conformational changes coupled to light-induced proton transfers in their photoactive sites, and that lateral helix-helix interactions with their cognate transducers' 4-helix bundle in the membrane relay these conformational changes into different states of the Htr proteins which regulate the down-stream phosphotransfer pathway. ^

Conditional expression of Sry, and Wnt4 by gene-targeting: Studies in sexual and skeletal development

Sry and Wnt4 cDNAs were individually introduced into the ubiquitously-expressed Rosa26 ( R26) locus by gene targeting in embryonic stem (ES) cells to create a conditional gene expression system in mice. In the targeted alleles, expression of these cDNAs should be blocked by a neomycin resistance selection cassette that is flanked by loxP sites. Transgene expression should be activated after the blocking cassette is deleted by Cre recombinase. ^ To test this conditional expression system, I have bred R26-stop- Sry and R26-stop-Wnt4 heterozygotes with a MisRII-Cre mouse line that expresses Cre in the gonads of both sexes. Analysis of these two types of bigenic heterozygotes indicated that their gonads developed normally like those of wild types. However, one XX R26-Sry/R26-Sry; MisR2-Cre/+ showed epididymis-like structures resembling those of males. In contrast, only normal phenotypes were observed in XY R26-Wnt4/R26-Wnt4; MisR2-Cre /+ mice. To interpret these results, I have tested for Cre recombinase activity by Southern blot and transcription of the Sry and Wnt4 transgenes by RT-PCR. Results showed that bigenic mutants had insufficient activation of the transgenes in their gonads at E12.5 and E13.5. Therefore, the failure to observe mutant phenotypes may have resulted from low activity of MisR2-Cre recombination at the appropriate time. ^ Col2a1-Cre transgenic mice express Cre in differentiating chondrocytes. R26-Wnt4; Col2a1-Cre bigenic heterozygous mice were found to exhibit a dramatic alteration in growth presumably caused by Wnt4 overexpression during chondrogenesis. R26-Wnt4; Col2a1-Cre mice exhibited dwarfism beginning approximately 10 days after birth. In addition, they also had craniofacial abnormalities, and had delayed ossification of the lumbar vertebrate and pelvic bones. Histological analysis of the growth plates of R26-Wnt4; Col2a1-Cre mice revealed less structural organization and a delay in onset of the primary and secondary ossification centers. Molecular studies confirmed that overexpression of Wnt4 causes decreased proliferation and early maturation of chondrocytes. In addition, R26-Wnt4; Col2a1-Cre mice had decreased expression of vascular endothelial growth factor (VEGF), suggesting that defects in vascularization may contribute to the dwarf phenotype. Finally, 9-month-old R26-Wnt4; Col2a1-Cre mice had significantly more fat cells in the marrow cavities of their metaphysis long bones, implying that long-term overexpression of Wnt4may cause bone marrow pathologies. In conclusion, Wnt4 was activated by Col2a1-Cre recombinase and was overexpressed in the growth plate, resulting in aberrant proliferation and differentiation of chondrocytes, and ultimately leads to dwarfism in mice. ^