An integrated molecular biology and computational approach to CYP1A1 expression in human brain

The cytochromes P450 comprise a superfamily of heme-containing mono-oxygenases. These enzymes metabolize numerous xenobiotics, but also play a role in metabolism of endogenous compounds. The P450 1A1 enzyme generally metabolizes polycyclic aromatic hydrocarbons, and its expression can be induced by aryl hydrocarbon receptor (AhR) activation. CYP1A1 is an exception to the generality that the majority of CYPs demonstrate highest expression in liver; CYP1Al is present in numerous extrahepatic tissues, including brain. This P450 has been observed in two forms, wildtype (WT) and brain variant (BV), arising from alternatively spliced mRNA transcripts. The CYP1A1 BV mRNA presented an exon deletion and was detected in human brain but not liver tissue of the same individuals. ^ Quantitative PCR analyses were performed to determine CYP1A1 WT and BV transcript expression levels in normal, bipolar disorder or schizophrenic groups. In our samples, we show that CYP1A1 BV mRNA, when present, is found alongside the full-length form. Furthermore, we demonstrate a significant decrease in expression of CYP1A1 in patients with bipolar disorder or schizophrenia. The expression level was not influenced by post-mortem interval, tissue pH, age, tobacco use, or lifetime antipsychotic medication load. ^ There is no indication of increased brain CYP1A1 expression in normal smokers versus non-smokers in these samples. We observed slightly increased CYP1A1 expression only in bipolar and schizophrenic smokers versus non-smokers. This may be indicative of complex interactions between neuronal chemical environments and AhR-mediated CYP1A1 induction in brain. ^ Structural homology modeling demonstrated that P450 1A1 BV has several alterations to positions/orientations of substrate recognition site residues compared to the WT isoform. Automated substrate docking was employed to investigate the potential binding of neurological signaling molecules and neurotropic drugs, as well as to differentiate specificities of the two P450 1A1 isoforms. We consistently observed that the BV isoform produced energetically favorable substrate dockings in orientations not observed for the same substrate in the WT isoform. These results demonstrated that structural differences, namely an expanded substrate access channel and active site, confer greater capacity for unique compound docking positions suggesting a metabolic profile distinct from the wildtype form for these test compounds. ^

Computational identification and functional validation of regulatory motifs in cartilage-expressed genes.

Chondrocyte gene regulation is important for the generation and maintenance of cartilage tissues. Several regulatory factors have been identified that play a role in chondrogenesis, including the positive transacting factors of the SOX family such as SOX9, SOX5, and SOX6, as well as negative transacting factors such as C/EBP and delta EF1. However, a complete understanding of the intricate regulatory network that governs the tissue-specific expression of cartilage genes is not yet available. We have taken a computational approach to identify cis-regulatory, transcription factor (TF) binding motifs in a set of cartilage characteristic genes to better define the transcriptional regulatory networks that regulate chondrogenesis. Our computational methods have identified several TFs, whose binding profiles are available in the TRANSFAC database, as important to chondrogenesis. In addition, a cartilage-specific SOX-binding profile was constructed and used to identify both known, and novel, functional paired SOX-binding motifs in chondrocyte genes. Using DNA pattern-recognition algorithms, we have also identified cis-regulatory elements for unknown TFs. We have validated our computational predictions through mutational analyses in cell transfection experiments. One novel regulatory motif, N1, found at high frequency in the COL2A1 promoter, was found to bind to chondrocyte nuclear proteins. Mutational analyses suggest that this motif binds a repressive factor that regulates basal levels of the COL2A1 promoter.

The biology and mechanism of chemoresistance of brain metastases

Primary brain neoplasms and metastases to the brain are generally resistant to systemic chemotherapy. The purpose of theses studies was to determine the mechanism(s) for this resistance. We have developed a model to study the biology of brain metastasis by injecting metastatic K1735 melanoma cells into the carotid artery of syngeneic C3H/HeN or nude mice. The resulting brain lesions are produced in the parenchyma of the brain. Mice with subcutaneous or brain melanoma lesions were treated intravenously with doxorubicin (DXR) (7 mg/kg). The s.c. lesions regressed in most of the mice whereas no therapeutic benefits were produced in mice with brain metastases. The intravenous injection of sodium fluorescine revealed that the blood-brain barrier (BBB) is intact in and around brain metastases smaller than 0.2 mm$\sp2$ but not in larger lesions, implying that the BBB is not a major obstacle for chemotherapy of brain metastases.^ Western blot and FACS analyses revealed that K1735 melanoma brain metastases expressed high levels of P-glycoprotein (P-gp) as compared to s.c. tumors or in vitro cultures. Similarly, K1735 cells from brain metastases expressed higher levels of mdrl mRNA. This increased expression of mdrl was due to adaptation to the local brain environment. We base this conclusion on the results of two studies. First, K1735 cells from brain metastases cultured for 7 days lost the high mdrl expression. Second, in crossover experiments K1735 cells from s.c. tumors (low mdrl expression) implanted into the brain exhibited high levels of mdrl expression whereas cells from brain metastases implanted s.c. lost the high level mdrl expression.^ To investigate the mechanism by which the brain environment upregulates mdrl expression of the K1735 cells we first studied the regulation of P-gp in brain endothelial cells. Since astrocytes are closely linked with the BBB we cocultured brain endothelial cells for 3 days with astrocytes. These endothelial cells expressed high levels of mdrl mRNA and protein whereas endothelial cells cocultured with endothelial cells or fibroblasts did not. We next cocultured K1735 melanoma cells with astrocytes. Here again, astrocytes (but not fibroblasts or tumor cells) uprelated the mdrl expression in K1735 tumor cells. This upregulation inversely correlated with intracellular drug accumulation and sensitivity to DXR.^ The data conclude that the resistance of melanoma brain metastases to chemotherapy is not due to an intact BBB but to the upregulation of the mdrl gene by the organ microenvironment, i.e., the astrocytes. This epigenetic mediated resistance to chemotherapy has wide implications for the therapy of brain metastases. ^

Ovarian cancer angiogenesis, biology and therapy

The progressive growth of epithelial ovarian cancer tumor is regulated by proangiogenic molecules and growth factors released by tumor cells and the microenvironment. Previous studies showed that the expression of interleukin-8 (IL-8) directly correlates with the progression of human ovarian carcinomas implanted into the peritoneal cavity of nude mice. We examined the expression level of IL-8 in archival specimens of primary human ovarian carcinoma from patients undergoing curative surgery by in situ mRNA hybridization technique. The expression of IL-8 was significantly higher in patients with stage III disease than in patients with stage I disease. To investigate the role of IL-8 in the progressive growth of ovarian cancer, we isolated high- and low-IL-8 producing clones from parental Hey-A8 human ovarian cancer cells, and compared their proliferative activity and tumorigenicity in nude mice. The effect of exogenous IL-8 and IL-8 neutralizing antibody on ovarian cancer cell proliferation was investigated. Finally, we studied the modulation of IL-8 expression in ovarian cancer cells by sense and antisense IL-8 expression vector transfection and its effect on proliferation and tumorigenicity. We concluded that IL-8 has a direct growth potentiating activity in human ovarian cancer cells. ^ The expression level of IL-8 directly correlates with disease progression of human ovarian cancer, but the mechanism of induction is unknown. Since hypoxia and acidic pH are common features in solid tumors, we determined whether hypoxic and acidic conditions could regulate the expression of IL-8. Culturing the human ovarian cancer cells in hypoxic or acidic medium led to a significant increase in IL-8 mRNA and protein. Hypoxic- and acidosis-mediated transient increase in IL-8 expression involved both transcriptional activation of the IL-8 gene and enhanced stability of the IL-8 mRNA. Furthermore, we showed that IL-8 transcription activation by hypoxia or acidosis required the cooperation of NF-κB and AP-1 binding sites. ^ Finally, we studied novel therapies against human ovarian cancer. First, we determined whether inhibition of the catalytic tyrosine kinase activity of the receptors for vascular endothelial growth factor/vascular permeability factor (VEGF/VPF) inhibits the formation of malignant ascites and the progressive growth of human ovarian carcinoma cells implanted into the peritoneal cavity of nude mice. Our results suggest that blockade of the VEGF/VPF receptor may be an efficient strategy to inhibit formation of malignant ascites and growth of VEGF/VPF-dependent human ovarian carcinomas. Secondly, we determined whether local sustained production of murine interferon-β could inhibit the growth of human ovarian cancer cells in the peritoneal cavity of nude mice. Our results showed that local production of IFN-β could inhibit the in vivo growth of human ovarian cancer cells by upregulating the expression of the inducible nitric oxide synthase (NOS) in host macrophages. ^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Organization of the inferotemporal cortex in the macaque monkey: Connections of areas PITv and CITvp

Visual cortex of macaque monkeys consists of a large number of cortical areas that span the occipital, parietal, temporal, and frontal lobes and occupy more than half of cortical surface. Although considerable progress has been made in understanding the contributions of many occipital areas to visual perceptual processing, much less is known concerning the specific functional contributions of higher areas in the temporal and frontal lobes. Previous behavioral and electrophysiological investigations have demonstrated that the inferotemporal cortex (IT) is essential to the animal's ability to recognize and remember visual objects. While it is generally recognized that IT consists of a number of anatomically and functionally distinct visual-processing areas, there remains considerable controversy concerning the precise number, size, and location of these areas. Therefore, the precise delineation of the cortical subdivisions of inferotemporal cortex is critical for any significant progress in the understanding of the specific contributions of inferotemporal areas to visual processing. In this study, anterograde and/or retrograde neuroanatomical tracers were injected into two visual areas in the ventral posterior and central portions of IT (areas PITv and CITvp) to elucidate the corticocortical connections of these areas with well known areas of occipital cortex and with less well understood regions of inferotemporal cortex. The locations of injection sites and the delineation of the borders of many occipital areas were aided by the pattern of interhemispheric connections, revealed following callosal transection and subsequent labeling with HRP. The resultant patterns of connections were represented on two-dimensional computational (CARET) and manual cortical maps and the laminar characteristics and density of the projection fields were quantified. The laminar and density features of these corticocortical connections demonstrate thirteen anatomically distinct subdivisions or areas distributed within the superior temporal sulcus and across the inferotemporal gyrus. These results serve to refine previous descriptions of inferotemporal areas, validate recently identified areas, and provide a new description of the hierarchical relationships among occipitotemporal cortical areas in macaques. ^

Potential REST Targets in Neural Stem Cells and Glioblastoma-Derived Stem Cells

Glioblastoma multiforme (GBM) tumors are the most common malignant primary brain tumors in adults. The current theory is that these tumors are caused by self-renewing glioblastoma-derived stem cells (GSCs). At the current time, the mechanisms that regulate self-renewal and other oncogenic properties of GSCs remain unknown. Recently, we found transcriptional repressor REST maintains self-renewal in neural stem cells (NSCs) and in GSCs. REST also regulates other oncogenic properties, such as apoptosis, invasion and proliferation. However, the mechanisms by which REST regulates these oncogenic properties are unknown. In an attempt to determine these mechanisms, we performed loss and gain-of-function experiments and genome-wide mRNA expression analysis in GSCs, and we were able to identify REST-regulated genes in GSCs. This was accomplished, after screening concordantly regulated genes in NSCs and GSCs, utilizing two RE1 databases, and setting two-fold expression as filters on the resulting genes. These results received further validation by qRT-PCR. Ingenuity Pathway Analysis (IPA) analysis further revealed the top REST target genes in GSCs were downstream targets of REST and/or involved in other cancers in other cell lines. IPA also revealed that many of the differentially-regulated genes identified in this study are involved in oncogenic properties seen in GBM, and which we believe are related to REST expression.