ChIPing the cistrome of PXR in mouse liver

The pregnane X receptor (PXR) is a key regulator of xenobiotic metabolism and disposition in liver. However, little is known about the PXR DNA-binding signatures in vivo, or how PXR regulates novel direct targets on a genome-wide scale. Therefore, we generated a roadmap of hepatic PXR bindings in the entire mouse genome [chromatin immunoprecipitation (ChIP)-Seq]. The most frequent PXR DNA-binding motif is the AGTTCA-like direct repeat with a 4bp spacer [direct repeat (DR)-4)]. Surprisingly, there are also high motif occurrences with spacers of a periodicity of 5 bp, forming a novel DR-(5n + 4) pattern for PXR binding. PXR-binding overlaps with the epigenetic mark for gene activation (histone-H3K4-di-methylation), but not with epigenetic marks for gene suppression (DNA methylation or histone-H3K27-tri-methylation) (ChIP-on-chip). After administering a PXR agonist, changes in mRNA of most PXR-direct target genes correlate with increased PXR binding. Specifically, increased PXR binding triggers the trans-activation of critical drug-metabolizing enzymes and transporters. The mRNA induction of these genes is absent in PXR-null mice. The current work provides the first in vivo evidence of PXR DNA-binding signatures in the mouse genome, paving the path for predicting and further understanding the multifaceted roles of PXR in liver

Characterization and Small RNA Content of Extracellular Vesicles in Follicular Fluid of Developing Bovine Antral Follicles.

Exosomes and microvesicles (i.e., extracellular vesicles: EVs) have been identified within ovarian follicular fluid and recent evidence suggests that EVs are able to elicit profound effects on ovarian cell function. While existence of miRNA within EVs has been reported, whether EV size and concentration as well as their cargos (i.e., proteins and RNA) change during antral follicle growth remains unknown. Extracellular vesicles isolated from follicular fluid of small, medium and large bovine follicles were similar in size, while concentration of EVs decreased progressively as follicle size increased. Electron microscopy indicated a highly purified population of the lipid bilayer enclosed vesicles that were enriched in exosome biomarkers including CD81 and Alix. Small RNA sequencing identified a large number of known and novel miRNAs that changed in the EVs of different size follicles. Ingenuity Pathway Analysis (IPA) indicated that miRNA abundant in small follicle EV preparations were associated with cell proliferation pathways, while those miRNA abundant in large follicle preparations were related to inflammatory response pathways. These studies are the first to demonstrate that EVs change in their levels and makeup during antral follicle development and point to the potential for a unique vesicle-mediated cell-to-cell communication network within the ovarian follicle

An RNA Interference Lethality Screen of the Human Druggable Genome to Identify Molecular Vulnerabilities in Epithelial Ovarian Cancer

Targeted therapies have been used to combat many tumor types; however, few have effectively improved the overall survival in women with epithelial ovarian cancer, begging for a better understanding of this deadly disease and identification of essential drivers of tumorigenesis that can be targeted effectively. Therefore, we used a loss-of-function screening approach to help identify molecular vulnerabilities that may represent key points of therapeutic intervention. We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting over 6,000 druggable genes and studied their effects on growth and/or survival of epithelial ovarian cancer (EOC) cell lines. The top 300 “hits” affecting the viability of A1847 cells were rescreened across additional EOC cell lines and non-tumorigenic, human immortalized ovarian epithelial cell lines. Fifty-three gene candidates were found to exhibit effects in all tumorigenic cell lines tested. Extensive validation of these hits refined the list to four high quality candidates (HSPA5, NDC80, NUF2, and PTN). Mechanistic studies show that silencing of three genes leads to increased apoptosis, while HSPA5 silencing appears to alter cell growth through G1 cell cycle arrest. Furthermore, two independent gene expression studies show that NDC80, NUF2 and PTN were significantly aberrantly overexpressed in serous adenocarcinomas. Overall, our functional genomics results integrated with the genomics data provide an important unbiased avenue towards the identification of prospective therapeutic targets for drug discovery, which is an urgent and unmet clinical need for ovarian cancer

MicroRNA Expression can be a Promising Strategy for the Detection of Barrett's Esophagus: A Pilot Study

Clinical and Translational Gastroenterology is an open-access journal published by Nature Publishing Group.Patient outcomes for esophageal adenocarcinoma (EAC) have not improved despite huge advances in endoscopic therapy because cancers are being diagnosed late. Barrett's esophagus (BE) is the primary precursor lesion for EAC, and thus the non-endoscopic molecular diagnosis of BE can be an important approach to improve EAC outcomes if robust biomarkers for timely diagnosis are identified. MicroRNAs (miRNAs) are tissue-specific novel biomarkers that regulate gene expression and may satisfy this requirement.The current work was supported by a pilot grant from the American Cancer Society (A.B. and L.K.C.), the American College of Gastroenterology Junior Faculty Development Award (A.B.) and grants from Hall Family Foundation (L.K.C.) and Kansas IDeA Network of Biomedical Research Excellence (A.B., L.K.C.). None of the funding bodies had any role in design, in the collection, analysis and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication

RNA Sequencing of Human Peripheral Nerve in Response to Injury: Distinctive Analysis of the Nerve Repair Pathways

The development of regenerative therapies for central nervous system diseases can likely benefit from an understanding of the peripheral nervous system repair process, particularly in identifying potential gene pathways involved in human nerve repair. This study employed RNA sequencing (RNA-seq) technology to analyze the whole transcriptome profile of the human peripheral nerve in response to an injury. The distal sural nerve was exposed, completely transected, and a 1 to 2 cm section of nerve fascicles was collected for RNA-seq from six participants with Parkinson\u27s disease, ranging in age between 53 and 70 yr. Two weeks after the initial injury, another section of the nerve fascicles of the distal and pre-degenerated stump of the nerve was dissected and processed for RNA-seq studies. An initial analysis between the pre-lesion status and the postinjury gene expression revealed 3,641 genes that were significantly differentially expressed. In addition, the results support a clear transdifferentiation process that occurred by the end of the 2-wk postinjury. Gene ontology (GO) and hierarchical clustering were used to identify the major signaling pathways affected by the injury. In contrast to previous nonclinical studies, important changes were observed in molecular pathways related to antiapoptotic signaling, neurotrophic factor processes, cell motility, and immune cell chemotactic signaling. The results of our current study provide new insights regarding the essential interactions of different molecular pathways that drive neuronal repair and axonal regeneration in humans

Regulation of Liver Regeneration by Hepatocyte O-GlcNAcylation in Mice

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Background & Aims The liver has a unique capacity to regenerate after injury in a highly orchestrated and regulated manner. Here, we report that O-GlcNAcylation, an intracellular post-translational modification regulated by 2 enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), is a critical termination signal for liver regeneration following partial hepatectomy (PHX). Methods We studied liver regeneration after PHX on hepatocyte specific OGT and OGA knockout mice (OGT-KO and OGA-KO), which caused a significant decrease (OGT-KO) and increase (OGA-KO) in hepatic O-GlcNAcylation, respectively. Results OGA-KO mice had normal regeneration, but the OGT-KO mice exhibited substantial defects in termination of liver regeneration with increased liver injury, sustained cell proliferation resulting in significant hepatomegaly, hepatic dysplasia, and appearance of small nodules at 28 days after PHX. This was accompanied by a sustained increase in expression of cyclins along with significant induction in pro-inflammatory and pro-fibrotic gene expression in the OGT-KO livers. RNA-sequencing studies revealed inactivation of hepatocyte nuclear 4 alpha (HNF4α), the master regulator of hepatic differentiation and a known termination signal, in OGT-KO mice at 28 days after PHX, which was confirmed by both Western blot and immunohistochemistry analysis. Furthermore, a significant decrease in HNFα target genes was observed in OGT-KO mice, indicating a lack of hepatocyte differentiation following decreased hepatic O-GlcNAcylation. Immunoprecipitation experiments revealed HNF4α is O-GlcNAcylated in normal differentiated hepatocytes. Conclusions These studies show that O-GlcNAcylation plays a critical role in the termination of liver regeneration via regulation of HNF4α in hepatocytes

Information categorisation in biological sequence alignments

This is a two-part report. In the first part we introduce the reader to biological sequence alignment. We discus dynamic programming as is used in sequence alignment, first in the case of two sequences and later, how it is adopted for multiple sequence alignment. Several references are given to the different sequence alignment strategies reported in the literature used to enhance the standard dynamic programming algorithm for sequence alignment to suit biological sequences. A short discussion on how alignments are scored is given. Finally, some of the existing sequence alignment tools are described.The second part of this report presents a critical analysis of information as it relates to biological sequence alignment. Information relating to the sequences being aligned form the basis on which any alignment is built. In its basic form this information might quantify how individual residues are scored when aligned with each other or how gaps are scored when introduced between two residues. Every biological sequence has if not explicit, at least some form of implicit information relating to its residues that form distinguishing markers along the sequence. There are many ways of extracting this information such as from databases of the relevant sequences, from the literature, prior processing etc. It is reasonable to assume that the more sequence information we use in an alignment, the more confidant we can be of the resulting alignment, and hence make better hypothesis of the unknown sequences. The aim of this part of the report is to build a framework on how to represent this information in such a way as to facilitate the dynamic and flexible incorporation of it to facilitate sequence alignments.</p

Computational Tools for Identifying Functional Regions in Biological Sequences

Automated biological sequence annotation is a rapidly developing field. The need for computational tools to facilitate this exercise is of stark necessity given the rate at which new genetic sequences are being accumulated. This dissertation introduces new approaches to two fundamental problems in contemporary bioinformatics, and their synergic integration. They are described in two parts: In Part I, we introduce a novel approach based on templates to differentiate between transcription factor binding sites and non-binding sites. Templates model three key discriminatory features, sequence homology, structural homology and nucleotide polymorphisms present in various degrees in different transcription factor binding sites. We show how templates can be adopted to predict the actual binding affinity of a given binding site based on the distribution of binding affinities of a set of training sites. We also present examples demonstrating the excellen-t discriminative and predictive capabilities of templates for transcription factor binding sites. In Part II, we introduce a new framework for sequence alignment. Here, information is seen as information units that act upon the sequences being aligned rather than an intrinsic part of the sequences themselves. The result is a versatile alignment tool, a tool that can dynamically incorporate knowledge on demand to a sequence alignment. We describe efficient data structures that form an integral part of such alignment tool. The described data structures are efficient in terms of both storage and retrieval of information. We illustrate a hybrid alignment strategy geared towards accommodating the diversity of information available on the sequences being aligned. The alignment algorithms described are optimised over a combination of both the alignment of individual residue pairs and the alignment of sequence segments. We present examples demonstrating the versatility of the described alignment framework and the high quality of alignments that it produces.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Finding transcription factor binding sites in DNA Sequences: A template based approach

A problem faced by many algorithms for finding transcription factor binding sites is the high number of false positive hits that result with the increased sensitivity of their prediction. A main contributing factor to this is the short and degenerate nature of these sites which results in a low signal to noise ratio. In order to counter this problem one needs to look beyond the base independence assumption. We propose a model based on templates designed to capture not only the vertical consensus but also the correlation of individual bases with the other bases of the site