Cis-acting elements and developmental regulators govern toxin gene expression in Bacillus anthracis

Expression of the structural genes for the anthrax toxin proteins is coordinately controlled by host-related signals such as elevated CO2 , and the trans-acting positive regulator, AtxA. No specific binding of AtxA to the toxin gene promoters has been demonstrated and no sequence-based similarities are apparent in the promoter regions of toxin genes. We hypothesized that the toxin genes possess common structural features that are required for positive regulation. To test this hypothesis, I performed an extensive characterization of the toxin gene promoters. I determined the minimal sequences required for atxA-mediated toxin gene expression and compared these sequences for structural similarities. In silico modeling and in vitro experiments indicated significant curvature within these regions. Random mutagenesis revealed that point mutations associated with reduced transcriptional activity, mostly mapped to areas of high curvature. This work enabled the identification of two potential cis-acting elements implicated in AtxA-mediated regulation of the toxin genes. In addition to the growth condition requirements and AtxA, toxin gene expression is under growth phase regulation. The transition state regulator AbrB represses atxA expression to influence toxin synthesis. Here I report that toxin gene expression also requires sigH, a gene encoding the RNA polymerase sigma factor associated with development in B. subtilis. In the well-studied B. subtilis system, σH is part of a feedback control pathway that involves AbrB and the major response regulator of sporulation initiation, Spo0A. My data indicate that in B. anthracis, regulatory relationships exist between these developmental regulators and atxA . Interestingly, during growth in toxin-inducing conditions, sigH and abrB expression deviates from that described for B. subtilis, affecting expression of the atxA gene. These findings, combined with previous observations, suggest that the steady state level of atxA expression is critical for optimal toxin gene transcription. I propose a model whereby, under toxin-inducing conditions, control of toxin gene expression is fine-tuned by the independent effects of the developmental regulators on the expression of atxA . The growth condition-dependent changes in expression of these regulators may be crucial for the correct timing and uninterrupted expression of the toxin genes during infection. ^

DNA nucleotide excision repair gene single nucleotide polymorphisms and hereditary nonpolyposis colorectal cancer

Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease caused by germline mutations in DNA mismatch repair(MMR) genes. The nucleotide excision repair(NER) pathway plays a very important role in cancer development. We systematically studied interactions between NER and MMR genes to identify NER gene single nucleotide polymorphism (SNP) risk factors that modify the effect of MMR mutations on risk for cancer in HNPCC. We analyzed data from polymorphisms in 10 NER genes that had been genotyped in HNPCC patients that carry MSH2 and MLH1 gene mutations. The influence of the NER gene SNPs on time to onset of colorectal cancer (CRC) was assessed using survival analysis and a semiparametric proportional hazard model. We found the median age of onset for CRC among MMR mutation carriers with the ERCC1 mutation was 3.9 years earlier than patients with wildtype ERCC1(median 47.7 vs 51.6, log-rank test p=0.035). The influence of Rad23B A249V SNP on age of onset of HNPCC is age dependent (likelihood ratio test p=0.0056). Interestingly, using the likelihood ratio test, we also found evidence of genetic interactions between the MMR gene mutations and SNPs in ERCC1 gene(C8092A) and XPG/ERCC5 gene(D1104H) with p-values of 0.004 and 0.042, respectively. An assessment using tree structured survival analysis (TSSA) showed distinct gene interactions in MLH1 mutation carriers and MSH2 mutation carriers. ERCC1 SNP genotypes greatly modified the age onset of HNPCC in MSH2 mutation carriers, while no effect was detected in MLH1 mutation carriers. Given the NER genes in this study play different roles in NER pathway, they may have distinct influences on the development of HNPCC. The findings of this study are very important for elucidation of the molecular mechanism of colon cancer development and for understanding why some mutation carriers of the MSH2 and MLH1 gene develop CRC early and others never develop CRC. Overall, the findings also have important implications for the development of early detection strategies and prevention as well as understanding the mechanism of colorectal carcinogenesis in HNPCC. ^

Anti-glomerular basement membrane glomerulonephritis: Characterization of an epitope, antibody response, and the potential role of IL-4Ralpha in disease progression

Anti-Glomerular Basement Membrane Glomerulonephritis (anti-GBM GM) is one of the earliest described autoimmune disorders. Patients present with proteinuria, anti-GBM antibodies, and renal failure. Studies have implicated a T Helper 1 (TH1) response in disease induction and a T Helper 2 (TH2) response for disease progression. A 13 amino acid long peptide sequence spanning residues 28 through 40 [pCol(28–40)] of the Collagen IV α3 non-collagen domain (Col IV α3 NCD) is immunogenic and induces anti-GBM GN. In order to fully understand disease initiation, this peptide was further characterized. Peptides were created containing one amino acid substitution for the entire length of pCol(28–40) and induction of anti-GBM GN was monitored. When residues 31, 33, or 34 contained the substitution, anti-GBM GN was unable to be induced. Thus, residues 31, 33, and 34 of pCol(28–40) are required for induction of anti-GBM. Glomerular injury is observed as early as 14 days post anti-GBM GN induction. However, the presence of anti-GBM antibodies is not observed until 20 days post immunization. An enlarged lymph node adjacent to the diseased kidney exhibits B cell activation after renal injury and produces antibodies toward GBM. Thus, anti-GBM antibodies are a consequence of the initial renal injury. Differences between disease susceptible and disease resistant rat strains exist in the expression of IL-4Rα, a major player in the TH2 response. IL-4Rα signaling is regulated by soluble IL-4Rα (sIL-4Rα). Low expression levels of sIL-4Rα result in the stabilization of IL-4 binding, while elevated expression sequesters IL-4. Quantitative PCR experiments noted low siL-4Rα expression levels in disease susceptible rats. Induction of an immune response toward sIL-4Rα in this strain was responsible for delayed disease progression in 15 out of the 17 experimental animals. Antibody transfer and in vivo biological activity experiments confirmed that delayed disease development was due to anti-sIL-4Rα antibodies. Together these experiments indicate that a T-cell epitope is required for activation of a TH1 autoimmune response and anti-GBM antibodies are a consequence of renal injury. More importantly, a role for IL-4Rα signaling is implicated in the progression of anti-GBM GN. ^

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

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.

Patenting genes and gene sequences: Analysis of public health implications and the law

At issue is whether or not isolated DNA is patent eligible under the U.S. Patent Law and the implications of that determination on public health. The U.S. Patent and Trademark Office has issued patents on DNA since the 1980s, and scientists and researchers have proceeded under that milieu since that time. Today, genetic research and testing related to the human breast cancer genes BRCA1 and BRCA2 is conducted within the framework of seven patents that were issued to Myriad Genetics and the University of Utah Research Foundation between 1997 and 2000. In 2009, suit was filed on behalf of multiple researchers, professional associations and others to invalidate fifteen of the claims underlying those patents. The Court of Appeals for the Federal Circuit, which hears patent cases, has invalidated claims for analyzing and comparing isolated DNA but has upheld claims to isolated DNA. The specific issue of whether isolated DNA is patent eligible is now before the Supreme Court, which is expected to decide the case by year's end. In this work, a systematic review was performed to determine the effects of DNA patents on various stakeholders and, ultimately, on public health; and to provide a legal analysis of the patent eligibility of isolated DNA and the likely outcome of the Supreme Court's decision. ^ A literature review was conducted to: first, identify principle stakeholders with an interest in patent eligibility of the isolated DNA sequences BRCA1 and BRCA2; and second, determine the effect of the case on those stakeholders. Published reports that addressed gene patents, the Myriad litigation, and implications of gene patents on stakeholders were included. Next, an in-depth legal analysis of the patent eligibility of isolated DNA and methods for analyzing it was performed pursuant to accepted methods of legal research and analysis based on legal briefs, federal law and jurisprudence, scholarly works and standard practice legal analysis. ^ Biotechnology, biomedical and clinical research, access to health care, and personalized medicine were identified as the principle stakeholders and interests herein. Many experts believe that the patent eligibility of isolated DNA will not greatly affect the biotechnology industry insofar as genetic testing is concerned; unlike for therapeutics, genetic testing does not require tremendous resources or lead time. The actual impact on biomedical researchers is uncertain, with greater impact expected for researchers whose work is intended for commercial purposes (versus basic science). The impact on access to health care has been surprisingly difficult to assess; while invalidating gene patents might be expected to decrease the cost of genetic testing and improve access to more laboratories and physicians' offices that provide the test, a 2010 study on the actual impact was inconclusive. As for personalized medicine, many experts believe that the availability of personalized medicine is ultimately a public policy issue for Congress, not the courts. ^ Based on the legal analysis performed in this work, this writer believes the Supreme Court is likely to invalidate patents on isolated DNA whose sequences are found in nature, because these gene sequences are a basic tool of scientific and technologic work and patents on isolated DNA would unduly inhibit their future use. Patents on complementary DNA (cDNA) are expected to stand, however, based on the human intervention required to craft cDNA and the product's distinction from the DNA found in nature. ^ In the end, the solution as to how to address gene patents may lie not in jurisprudence but in a fundamental change in business practices to provide expanded licenses to better address the interests of the several stakeholders. ^

IL -24; a glycosylated dimeric cytokine affecting monocytes and cytotoxic to melanoma cells

IL-24 is an unusual member of the IL-10 family, which is considered a Th1 cytokine that exhibits tumor cell cytotoxicity. I describe the purification of this novel cytokine from the supernatant of IL-24 gene transfected human embryonic kidney cells and define the biochemical and functional properties of the soluble, human IL-24 protein. ^ I showed IL-24 non-covalently associates with bovine albumin. Immunoaffinity purification followed by cation exchange chromatography resulted in the significant enrichment of N-glycosylated IL-24. This protein elicited dose-dependent secretion of TNF-α and IL-6 from purified human monocytes and TNF-α secretion from PMA differentiated U937 cells. I showed this same protein was cytotoxic to melanoma tumor cells via the induction of IFN-α. ^ I reported IL-24 associates as at least two disulfide linked, N-glycosylated dimers. Enzymatic removal of N-linked-glycosylation from purified IL-24 partially diminished its cytokine and cytotoxic functions. Disruption of IL-24 dimers via reduction and alkylation of intermolecular disulfide bonds nearly abolished IL-24s cytokine function. ^ I elucidated IL-24 induced TNF-α secretion was pSTAT1, pSTAT3 as well as the class II heterodimeric receptors IL-20R1/IL-22R2 independent. I identified a requirement for the heterodimer of Toll-like Receptors 1 and 2 for IL-24s cytokine function and show a physical interaction between IL-24 and the extracellular domain of TLR-1. ^ Thus, I demonstrated that purified N-glycosylated, soluble, dimeric, human IL-24 exhibits both immunomodulatory and anti-cancer activities and these functions remain associated during purification. IL-24 induced TNF-α secretion required an interaction with the heterodimeric receptor TLR-1/2 and IL-24s cytotoxic affect to melanoma tumor cells was in part due to its induction of IFN-β. ^