Cryo-EM model of the bullet-shaped vesicular stomatitis virus.

Vesicular stomatitis virus (VSV) is a bullet-shaped rhabdovirus and a model system of negative-strand RNA viruses. Through direct visualization by means of cryo-electron microscopy, we show that each virion contains two nested, left-handed helices: an outer helix of matrix protein M and an inner helix of nucleoprotein N and RNA. M has a hub domain with four contact sites that link to neighboring M and N subunits, providing rigidity by clamping adjacent turns of the nucleocapsid. Side-by-side interactions between neighboring N subunits are critical for the nucleocapsid to form a bullet shape, and structure-based mutagenesis results support this description. Together, our data suggest a mechanism of VSV assembly in which the nucleocapsid spirals from the tip to become the helical trunk, both subsequently framed and rigidified by the M layer.

Protein-protein interaction between phototaxis receptor sensory Rhodopsin I and its transducer HtrI

The molecular complex containing the seven transmembrane helix photoreceptor S&barbelow;ensory R&barbelow;hodopsin I&barbelow; (SRI) and transducer protein HtrI (H&barbelow;alobacterial Transducer for SRI&barbelow;) mediates color-sensitive phototaxis responses in the archaeon Halobacterium salinarum. Orange light causes an attractant response by a one-photon reaction and white light (orange + UV light) a repellent response by a two-photon reaction. Three aspects of SRI-HtrI structure/function and the signal transduction pathway were explored. First, the coupling of HtrI to the photoactive site of SRI was analyzed by mutagenesis and kinetic spectroscopy. Second, SRI-HtrI mutations and suppressors were selected and characterized to elucidate the color-sensing mechanism. Third, the signal relay through the transducer-bound histidine kinase was analyzed using an in vitro reconstitution system with known and newly identified taxis components. ^ Twenty-one mutations on HtrI were introduced by site-directed mutagenesis. Several replacements of charged residues perturbed the photochemical kinetics of SRI which led to the finding of a cluster of residues at the membrane/cytoplasm interface in HtrI electrostatically coupled to the photoactive site of SRI. We found by laser-flash kinetic spectroscopy that the transducer and these residues have specific effects on the light-induced proton transfer between the retinal chromophore and the protein. ^ One of the mutations showed an unusual mutant phenotype we called “inverted” signaling, in which the cell produces a repellent response to normally attractant light. Therefore, this mutant (E56Q of HtrI) had lost the color-discrimination by the SRI-HtrI complex. We used suppressor analysis to better understand the phenotype. Certain suppressors resulted in return of attractant responses to orange light but with inversion of the normally repellent response to white light to an attractant response. To explain this and other results, we formulated the Conformational Shuttling model in which the HtrI-SRI complex is poised in a metastable equilibrium of two conformations shifted in opposite directions by orange and white light. We tested this model by behavioral analysis (computerized cell tracking and motion study) of double mutants of inverting and suppressing mutations and the results confirmed the equilibrium-shift explanation. ^ We developed an in vitro system for measuring the effect of purified transducer on the histidine-kinase CheAH that controls the flagellar motor switch. The rate of kinase autophosphorylation was stimulated >2 fold in the reconstitution of the complete signal transduction system from purified components from H. salinarum. The in vitro assay also showed that the kinase activity was reduced in the absence and in the presence of high levels of linker protein CheWH. (Abstract shortened by UMI.) ^

Theory of uncertainty in illness in patients with cancer of unknown primary origin: Structure providers as antecedents of uncertainty in a population of cancer patients with an unknown primary diagnosis

Uncertainty has been found to be a major component of the cancer experience and can dramatically affect psychosocial adaptation and outcomes of a patient's disease state (McCormick, 2002). Patients with a diagnosis of Carcinoma of Unknown Primary (CUP) may experience higher levels of uncertainty due to the unpredictability of current and future symptoms, limited treatment options and an undetermined life expectancy. To date, only one study has touched upon uncertainty and its' effects on those with CUP but no information exists concerning the effects of uncertainty regarding diagnosis and treatment on the distress level and psychosocial adjustment of this population (Parker & Lenzi, 2003). ^ Mishel's Uncertainty in Illness Theory (1984) proposes that uncertainty is preceded by three variables, one of which being Structure Providers. Structure Providers include credible authority, the degree of trust and confidence the patient has with their doctor, education and social support. It was the goal of this study to examine the relationship between uncertainty and Structure Providers to support the following hypotheses: (1) There will be a negative association between credible authority and uncertainty, (2) There will be a negative association between education level and uncertainty, and (3) There will be a negative association between social support and uncertainty. ^ This cross-sectional analysis utilized data from 219 patients following their initial consultation with their oncologist. Data included the Mishel Uncertainty in Illness Scale (MUIS) which was used to determine patients' uncertainty levels, the Medical Outcomes Study-Social Support Scale (MOSS-SSS) to assess patients, levels of social support, the Patient Satisfaction Questionnaire (PSQ-18) and the Cancer Diagnostic Interview Scale (CDIS) to measure credible authority and general demographic information to assess age, education, marital status and ethnicity. ^ In this study we found that uncertainty levels were generally higher in this sample as compared to other types of cancer populations. And while our results seemed to support most of our hypothesis, we were only able to show significant associations between two. The analyses indicated that credible authority measured by both the CDIS and the PSQ was a significant predictor of uncertainty as was social support measured by the MOSS-SS. Education has shown to have an inconsistent pattern of effect in relation to uncertainty and in the current study there was not enough data to significantly support our hypothesis. ^ The results of this study generally support Mishel's Theory of Uncertainty in Illness and highlight the importance of taking into consideration patients, psychosocial factors as well as employing proper communication practices between physicians and their patients.^

An assessment of obesity and hyperphagia in individuals with Smith-Magenis syndrome

Smith-Magenis syndrome (SMS;OMIM# 182290) is a multiple congenital anomalies and mental retardation syndrome caused by a 3.7- Mb deletion on chromosome 17p11.2 or a mutation in the RAI1 gene. Although the majority of the SMS phenotype has been well described, limited studies are available describing growth patterns in SMS. There is some evidence that individuals with SMS develop obesity. Thus, this study aims to characterize the growth and potential influence of hyperphagia in a cohort of individuals with SMS. A retrospective chart review was conducted of 78 individuals with SMS through Baylor College of Medicine (BCM) at Texas Children¡¯s Hospital (TCH.) All documented height and weight measurements were abstracted and Z-scores (SD units) for height-for-age, length-for-age and BMI-for-age were calculated. Mail-out questionnaires were provided to the corresponding parents of the cohort to assess for the presence of hyperphagia through a validated hyperphagia questionnaire (HQ). Analysis of this data demonstrates that by the age ¡Ý 20 years males with SMS have mean BMI¡¯s in the 85th-90th percentile corresponding to an overweight BMI, and females with SMS had mean BMI¡¯s in the 95th -97th percentile corresponding to an obese BMI. Parents indicated that hyperphagia is present in individuals with SMS as 76% of parent¡¯s report having to lock food away from their child. Females¡¯ age ¡Ý 20 years of age had the highest mean behavior, drive and severity scores as well as the highest BMI. Thus, this study concludes that it appears overweight and obesity, as well as hyperphagia, are present in this cohort of SMS individuals. The results of this study will hopefully enable parents and caregivers of children with SMS to take preventative measures in order to control food related behaviors present in their children as well as to prevent overweight and obesity and the associated negative health consequences.

Smooth Muscle Hyperplasia due to ACTA2/MYH11 Mutations: Identification of Novel Pathology and Pathways Leading to Aneurysms and Diverse Vascular Occlusive Diseases

Missense mutations in smooth muscle cell (SMC) specific ACTA2 (á-actin) and MYH11 (â-myosin heavy chain) cause diffuse and diverse vascular diseases, including thoracic aortic aneurysms and dissections (TAAD) and early onset coronary artery disease and stroke. The mechanism by which these mutations lead to dilatation of some arteries but occlusion of others is unknown. We hypothesized that the mutations act through two distinct mechanisms to cause varied vascular diseases: a loss of function, leading to decreased SMC contraction and aneurysms, and a gain of function, leading to increased SMC proliferation and occlusive disease. To test this hypothesis, ACTA2 mutant SMCs and myofibroblasts were assessed and found to not form á-actin filaments whereas control cells did, suggesting a dominant negative effect of ACTA2 mutations on filament formation. A loss of á-actin filaments would be predicted to cause decreased SMC contractility. Histological examination of vascular tissues from patients revealed SMC hyperplasia leading to arterial stenosis and occlusion, supporting a gain of function associated with the mutant gene. Furthermore, ACTA2 mutant SMCs and myofibroblasts proliferated more rapidly in static culture than control cells (p<0.05). We also determined that Acta2-/- mice have ascending aortic aneurysms. Histological examination revealed aortic medial SMC hyperplasia, but minimal features of medial degeneration. Acta2-/- SMCs proliferated more rapidly in culture than wildtype (p<0.05), and microarray analysis of Acta2-/- SMCs revealed increased expression of Actg2, 15 collagen genes, and multiple focal adhesion genes. Acta2-/- SMCs showed altered localization of vinculin and zyxin and increased phosphorylated focal adhesion kinase (FAK) in focal adhesions. A specific FAK inhibitor decreased Acta2-/- SMC proliferation to levels equal to wildtype SMCs (p<0.05), suggesting that FAK activation leads to the increased proliferation. We have described a unique pathology associated with ACTA2 and MYH11 mutations, as well as an aneurysm phenotype in Acta2-/- mice. Additionally, we identified a novel pathogenic pathway for vascular occlusive disease due to loss of SMC contractile filaments, alterations in focal adhesions, and activation of FAK signaling in SMCs with ACTA2 mutations.

LONGITUDINAL GROWTH PARAMETERS AND THEIR ECOLOGICAL DETERMINANTS (SEASONALITY)

The growth patterns of weight from birth through the first twelve months of life among rural Taiwanese infants were investigated with the following objectives: (i) compare each of the parameters of the Count model estimated for infants who were nutritionally at risk with those for a reference population from the United States; and (ii) within the Taiwanese infants, account for the variance in the growth patterns in the first and second six months of life on the basis of selected ecological factors.^ The significance between group differences were observed in the patterns of the weight growth in both linear growth and in the timing and the direction of velocity changes. A significant decline in growth velocity was observed among Taiwanese infants at about the fourth month of life. The decline is in keeping with a recent proposal made by J. C. Waterlow regarding the timing of change in growth velocity among nutritionally at risk populations in developing countries. The growth course of a nutritionally at risk infant during the first three months is apparently protected by the nurturance of the mother and innate biological properties of the infant.^ A highly significant portion of the growth variance in the second six months of life was accounted for by exogenous factors and biological factors related to the infant. Conversely, none of the growth variance in the first six months of life was accounted for by predictor variables. The most potent determinant of growth in the second six months of life was seasonality which represents a multiple environmental event.^ The model parameters estimated from the Count model represent different aspect of physical growth; yet the correlation coefficients between parameters b and c are high (r > .80). Clearly, the biological interpretation of the model parameters requires analysis of the whole function in the specific context of a given age period. ^

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.