Rubisco in complex with Rubisco large subunit methyltransferase.

SET domain protein lysine methyltransferases (PKMT) are a structurally unique class of enzymes that catalyze the specific methylation of lysine residues in a number of different substrates. Especially histone-specific SET domain PKMTs have received widespread attention because of their roles in the regulation of epigenetic gene expression and the development of some cancers. Rubisco large subunit methyltransferase (RLSMT) is a chloroplast-localized SET domain PKMT responsible for the formation of trimethyl-lysine-14 in the large subunit of Rubisco, an essential photosynthetic enzyme. Here, we have used cryoelectron microscopy to produce an 11-A density map of the Rubisco-RLSMT complex. The atomic model of the complex, obtained by fitting crystal structures of Rubisco and RLSMT into the density map, shows that the extensive contact regions between the 2 proteins are mainly mediated by hydrophobic residues and leucine-rich repeats. It further provides insights into potential conformational changes that may occur during substrate binding and catalysis. This study presents the first structural analysis of a SET domain PKMT in complex with its intact polypeptide substrate.

Correlation between dental care utilization and oral cavity cancer in a large sample of community-based United States residents

Cancer of the oral cavity and pharynx remains one of the ten leading causes of cancer death in the United States (US). Besides smoking and alcohol consumption, there are no well established risk factors. While poor dental care had been implicated, it is unknown if the lack of dental care, implying poor dental hygiene predisposes to oral cavity cancer. This study aimed to assess the relationship between dental care utilization during the past twelve months and the prevalence of oral cavity cancer. A cross-sectional design of the National Health Interview Survey of adult, non-institutionalized US residents (n=30,475) was used to assess the association between dental care utilization and self reported diagnosis of oral cavity cancer. Chi square statistic was used to examine the crude association between the predictor variable, dental care utilization and other covariates, while unconditional logistic regression was used to assess the relationship between oral cavity cancer and dental care utilization. There were statistically significant differences between those who utilized dental care during the past twelve months and those who did not with respect to education, income, age, marital status, and gender (p < 0.05), but not health insurance coverage (p = 0.53). Also, those who utilized dental care relative to those who did not were 65% less likely to present with oral cavity cancer, prevalence odds ratio (POR), 0.35, 95% Confidence Interval (CI), 0.12–0.98. Further, higher income advanced age, people of African heritage, and unmarried status were statistically significantly associated with oral cavity cancer, (p < 0.05), but health insurance coverage, alcohol use and smoking were not, p > 0.05. However, after simultaneously controlling for the relevant covariates, the association between dental care and oral cavity cancer did not attenuate nor persist. Thus, compared with those who did not use dental care, those who did wee 62% less likely to present with oral cavity cancer adjusted POR, 0.38, 95% CI, 0.13-1.10. Among US adults residing in community settings, use of dental care during the past twelve months did not significantly reduce the predisposition to oral cavity cancer. However, due to the nature of the data used in this study, which restricts temporal sequence, a large sample prospective study that may identify modifiable factors associated with oral cancer development namely poor dental care, is needed. ^

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Dysregulation of alternative splicing of coagulation factor V results in bleeding disorder, east Texas type and other disorders of hemostasis

The studies completed herein explore different phenotypes related to the genetic defects that predispose individuals to a disruption of normal hemostasis. In the first study, a novel autosomal dominant bleeding disorder, which is characterized by excessive bleeding with trauma or surgery and menorrhagia in affected women, was studied in a large family (16 affected individuals) from east Texas. Affected members had a prolongation of their PT and/or aPTT, but normal clinical coagulation studies. Previous linkage analysis by Kuang et. al. (2001) mapped the defective gene to 1g23-24 (LODmax 7.22), which contains the gene for coagulation factor V (FV). I identified an alteration (A2440G) in the FV gene in exon 13 that segregated with the disease and was not present in 62 controls. Interestingly, this alteration resulted in a 22-fold up-regulation of a novel alternative splicing variant in patients' RNA versus controls. This translated into a similar fold increase in a 250-kDa isoform of FV seen in patients' plasma versus controls. A recombinant of this splicing event exhibited an increased sensitivity to cleavage by activated protein C (APC) that was more striking in the presence of PS. In addition, this novel isoform had increased APC cofactor activity, thus increasing the degradation of FVIIIa. These data indicated that A2440G up-regulates an alternatively spliced transcript of FV, and increases a FV isoform that hinders coagulation as opposed to promoting it like its wild-type counterpart. ^ The second study reports the largest screening to date of African Americans in two independent cohorts for a rare prothrombin variant, C20209T, which is suspected to be associated with thrombotic disease. The Texas Medical Center Genetics Resource (TexGen) Stroke DNA repository revealed 1.67% (Fisher p=0.27) of African American stroke patients were heterozygous for the 20209*T allele. Screening of the Atherosclerosis Risk in Communities Study (ARIC) cohort (n=3470) for the 20209*T allele revealed a population prevalence of 0.58% in individuals of African American descent; however, all associations with thrombotic disease were negative. Analysis of these two independent cohorts revealed that, unlike its neighbor G20210A, the C20209T variant does not increase the risk of thrombotic events in the African American population. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

The role of Ski/Sno oncoproteins as negative regulators of the TGF-beta/SMAD signaling pathway in B -cell non -Hodgkin's lymphoma (NHL-B)

Non-Hodgkin's lymphomas are common tumors of the human immune system, primarily of B cell lineage (NHL-B). Negative growth regulation in the B cell lineage is mediated primarily through the TGF-β/SMAD signaling pathway that regulates a variety of tumor suppressor genes. Ski was originally identified as a transforming oncoprotein, whereas SnoN is an isoform of the Sno protein that shares a large region of homology with Ski. In this study, we show that Ski/SnoN are endogenously over-expressed both in patients' lymphoma cells and NHL-B cell lines. Exogenous TGF-β1 treatment induces down-regulation of Ski and SnoN oncoprotein expression in an NHL-B cell line, implying that Ski and SnoN modulate the TGF-β signaling pathway and are involved in cell growth regulation. Furthermore, we have developed an NHL-B cell line (DB) that has a null mutation in TGF-β receptor type II. In this mutant cell line, Ski/SnoN proteins are not down-regulated in response to TGF-β1 treatment, suggesting that downregulation of Ski and SnoN proteins in NHL-B require an intact functional TGF-β signaling pathway Resting normal B cells do not express Ski until activated by antigens and exogenous cytokines, whereas a low level of SnoN is also present in peripheral blood Go B cells. In contrast, autonomously growing NHL-B cells over-express Ski and SnoN, implying that Ski and SnoN are important cell cycle regulators. To further investigate a possible link between reduction of the Ski protein level and growth inhibition, Ski antisense oligodeoxynucleotides were transfected into NHL-B cells. The Ski protein level was found to decrease to less than 40%, resulting in restoring the effect of TGF-β and leading to cell growth inhibition and G1 cell cycle arrest. Co-immunoprecipitation experiments demonstrated that Ski associates with Smad4 in the nucleus, strongly suggesting that over-expression of the nuclear protein Ski and/or SnoN negatively regulates the TGF-β pathway, possibly by modulating Smad-mediated tumor suppressor gene expression. Together, in NHL-B, the TGF-β/SMAD growth inhibitory pathway is usually intact, but over-expression of the Ski and/or SnoN, which binds to Smad4, abrogates the negative regulatory effects of TGF-β/SMAD in lymphoma cell growth and potentiates the growth potential of neoplastic B cells. ^