Publications by authors named "Neil J McKenna"

38 Publications

A human liver chimeric mouse model for non-alcoholic fatty liver disease.

JHEP Rep 2021 Jun 21;3(3):100281. Epub 2021 Mar 21.

Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC, USA.

Background & Aims: The accumulation of neutral lipids within hepatocytes underlies non-alcoholic fatty liver disease (NAFLD), which affects a quarter of the world's population and is associated with hepatitis, cirrhosis, and hepatocellular carcinoma. Despite insights gained from both human and animal studies, our understanding of NAFLD pathogenesis remains limited. To better study the molecular changes driving the condition we aimed to generate a humanised NAFLD mouse model.

Methods: We generated TIRF (transgene-free //) mice, populated their livers with human hepatocytes, and fed them a Western-type diet for 12 weeks.

Results: Within the same chimeric liver, human hepatocytes developed pronounced steatosis whereas murine hepatocytes remained normal. Unbiased metabolomics and lipidomics revealed signatures of clinical NAFLD. Transcriptomic analyses showed that molecular responses diverged sharply between murine and human hepatocytes, demonstrating stark species differences in liver function. Regulatory network analysis indicated close agreement between our model and clinical NAFLD with respect to transcriptional control of cholesterol biosynthesis.

Conclusions: These NAFLD xenograft mice reveal an unexpected degree of evolutionary divergence in food metabolism and offer a physiologically relevant, experimentally tractable model for studying the pathogenic changes invoked by steatosis.

Lay Summary: Fatty liver disease is an emerging health problem, and as there are no good experimental animal models, our understanding of the condition is poor. We here describe a novel humanised mouse system and compare it with clinical data. The results reveal that the human cells in the mouse liver develop fatty liver disease upon a Western-style fatty diet, whereas the mouse cells appear normal. The molecular signature (expression profiles) of the human cells are distinct from the mouse cells and metabolic analysis of the humanised livers mimic the ones observed in humans with fatty liver. This novel humanised mouse system can be used to study human fatty liver disease.
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http://dx.doi.org/10.1016/j.jhepr.2021.100281DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138774PMC
June 2021

Steroid receptor coactivator 3 (SRC-3/AIB1) is enriched and functional in mouse and human Tregs.

Sci Rep 2021 Feb 9;11(1):3441. Epub 2021 Feb 9.

Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.

A subset of CD4 + lymphocytes, regulatory T cells (Tregs), are necessary for central tolerance and function as suppressors of autoimmunity against self-antigens. The SRC-3 coactivator is an oncogene in multiple cancers and is capable of potentiating numerous transcription factors in a wide variety of cell types. Src-3 knockout mice display broad lymphoproliferation and hypersensitivity to systemic inflammation. Using publicly available bioinformatics data and directed cellular approaches, we show that SRC-3 also is highly enriched in Tregs in mice and humans. Human Tregs lose phenotypic characteristics when SRC-3 is depleted or pharmacologically inhibited, including failure of induction from resting T cells and loss of the ability to suppress proliferation of stimulated T cells. These data support a model for SRC-3 as a coactivator that actively participates in protection from autoimmunity and may support immune evasion of cancers by contributing to the biology of Tregs.
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http://dx.doi.org/10.1038/s41598-021-82945-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873281PMC
February 2021

Consensus transcriptional regulatory networks of coronavirus-infected human cells.

Sci Data 2020 09 22;7(1):314. Epub 2020 Sep 22.

The Signaling Pathways Project and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA.

Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
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http://dx.doi.org/10.1038/s41597-020-00628-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509801PMC
September 2020

A transcriptional regulatory atlas of coronavirus infection of human cells.

bioRxiv 2020 May 14. Epub 2020 May 14.

The Signaling Pathways Project and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030.

Identifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over 3,000,000 data points from publically archived CoV infection transcriptomic datasets into consensus regulatory signatures, or consensomes, that rank genes based on their transcriptional responsiveness to infection of human cells by MERS, SARS-CoV-1 and SARS-CoV-2 subtypes. We computed overlap between genes with elevated rankings in the CoV consensomes against those from transcriptomic and ChIP-Seq consensomes for nearly 880 cellular signaling pathway nodes. Validating the CoV infection consensomes, we identified robust overlap between their highly ranked genes and high confidence targets of signaling pathway nodes with known roles in CoV infection. We then developed a series of use cases that illustrate the utility of the CoV consensomes for hypothesis generation around mechanistic aspects of the cellular response to CoV infection. We make the CoV infection datasets and their universe of underlying data points freely accessible through the Signaling Pathways Project web knowledgebase at https://www.signalingpathways.org/datasets/index.jsf.
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http://dx.doi.org/10.1101/2020.04.24.059527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263508PMC
May 2020

No Dataset Left Behind: Mechanistic Insights into Thyroid Receptor Signaling Through Transcriptomic Consensome Meta-Analysis.

Thyroid 2020 04 29;30(4):621-639. Epub 2020 Jan 29.

The Signaling Pathways Project, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas.

Discovery-scale omics datasets relevant to thyroid receptors (TRs) and their physiological and synthetic bioactive small-molecule ligands allow for genome-wide interrogation of TR-regulated genes. These datasets have considerable collective value as a reference resource to allow researchers to routinely generate hypotheses addressing the mechanisms underlying the cell biology and physiology of TR signaling in normal and disease states. Here, we searched the Gene Expression Omnibus database to identify a population of publicly archived transcriptomic datasets involving genetic or pharmacological manipulation of either TR isoform in a mouse tissue or cell line. After initial quality control, samples were organized into contrasts (experiments), and transcript differential expression values and associated measures of significance were generated and committed to a consensome (for consensus omics) meta-analysis pipeline. To gain insight into tissue-selective functions of TRs, we generated liver- and central nervous system (CNS)-specific consensomes and identified evidence for genes that were selectively responsive to TR signaling in each organ. The TR transcriptomic consensome ranks genes based on the frequency of their significant differential expression over the entire group of experiments. The TR consensome assigns elevated rankings both to known TR-regulated genes and to genes previously uncharacterized as TR-regulated, which shed mechanistic light on known cellular and physiological roles of TR signaling in different organs. We identify evidence for unreported genomic targets of TR signaling for which it exhibits strikingly distinct regulatory preferences in the liver and CNS. Moreover, the intersection of the TR consensome with consensomes for other cellular receptors sheds light on transcripts potentially mediating crosstalk between TRs and these other signaling paradigms. The mouse TR datasets and consensomes are freely available in the Signaling Pathways Project website for hypothesis generation, data validation, and modeling of novel mechanisms of TR regulation of gene expression. Our results demonstrate the insights into the mechanistic basis of thyroid hormone action that can arise from an ongoing commitment on the part of the research community to the deposition of discovery-scale datasets.
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http://dx.doi.org/10.1089/thy.2019.0307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187985PMC
April 2020

The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways.

Sci Data 2019 10 31;6(1):252. Epub 2019 Oct 31.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, 77030, USA.

Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus 'omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org .
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http://dx.doi.org/10.1038/s41597-019-0193-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823428PMC
October 2019

Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop.

J Biomed Inform 2017 07 10;71:49-57. Epub 2017 May 10.

Department of Pharmacological Sciences, BD2K-LINCS Data Coordination and Integration Center, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA. Electronic address:

The volume and diversity of data in biomedical research have been rapidly increasing in recent years. While such data hold significant promise for accelerating discovery, their use entails many challenges including: the need for adequate computational infrastructure, secure processes for data sharing and access, tools that allow researchers to find and integrate diverse datasets, and standardized methods of analysis. These are just some elements of a complex ecosystem that needs to be built to support the rapid accumulation of these data. The NIH Big Data to Knowledge (BD2K) initiative aims to facilitate digitally enabled biomedical research. Within the BD2K framework, the Commons initiative is intended to establish a virtual environment that will facilitate the use, interoperability, and discoverability of shared digital objects used for research. The BD2K Commons Framework Pilots Working Group (CFPWG) was established to clarify goals and work on pilot projects that address existing gaps toward realizing the vision of the BD2K Commons. This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States.
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http://dx.doi.org/10.1016/j.jbi.2017.05.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545976PMC
July 2017

Discovering relationships between nuclear receptor signaling pathways, genes, and tissues in Transcriptomine.

Sci Signal 2017 Apr 25;10(476). Epub 2017 Apr 25.

NURSA Informatics, Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.

We previously developed a web tool, Transcriptomine, to explore expression profiling data sets involving small-molecule or genetic manipulations of nuclear receptor signaling pathways. We describe advances in biocuration, query interface design, and data visualization that enhance the discovery of uncharacterized biology in these pathways using this tool. Transcriptomine currently contains about 45 million data points encompassing more than 2000 experiments in a reference library of nearly 550 data sets retrieved from public archives and systematically curated. To make the underlying data points more accessible to bench biologists, we classified experimental small molecules and gene manipulations into signaling pathways and experimental tissues and cell lines into physiological systems and organs. Incorporation of these mappings into Transcriptomine enables the user to readily evaluate tissue-specific regulation of gene expression by nuclear receptor signaling pathways. Data points from animal and cell model experiments and from clinical data sets elucidate the roles of nuclear receptor pathways in gene expression events accompanying various normal and pathological cellular processes. In addition, data sets targeting non-nuclear receptor signaling pathways highlight transcriptional cross-talk between nuclear receptors and other signaling pathways. We demonstrate with specific examples how data points that exist in isolation in individual data sets validate each other when connected and made accessible to the user in a single interface. In summary, Transcriptomine allows bench biologists to routinely develop research hypotheses, validate experimental data, or model relationships between signaling pathways, genes, and tissues.
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http://dx.doi.org/10.1126/scisignal.aah6275DOI Listing
April 2017

Improving the discoverability, accessibility, and citability of omics datasets: a case report.

J Am Med Inform Assoc 2017 03;24(2):388-393

Nuclear Receptor Signaling Atlas Informatics Hub, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.

Although omics datasets represent valuable assets for hypothesis generation, model testing, and data validation, the infrastructure supporting their reuse lacks organization and consistency. Using nuclear receptor signaling transcriptomic datasets as proof of principle, we developed a model to improve the discoverability, accessibility, and citability of published omics datasets. Primary datasets were retrieved from archives, processed to extract data points, then subjected to metadata enrichment and gap filling. The resulting secondary datasets were exposed on responsive web pages to support mining of gene lists, discovery of related datasets, and single-click citation integration with popular reference managers. Automated processes were established to embed digital object identifier-driven links to the secondary datasets in associated journal articles, small molecule and gene-centric databases, and a dataset search engine. Our model creates multiple points of access to reprocessed and reannotated derivative datasets across the digital biomedical research ecosystem, promoting their visibility and usability across disparate research communities.
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http://dx.doi.org/10.1093/jamia/ocw096DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7651888PMC
March 2017

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling.

Mol Endocrinol 2016 Aug 13;30(8):937-48. Epub 2016 Jul 13.

Departments of Molecular and Cellular Biology (S.A.O., J.D., C.C., N.J.M.) and Lester and Sue Smith Breast Center (A.T.) and the Nuclear Receptor Signaling Atlas Informatics Group (S.A.O., N.J.M.), Baylor College of Medicine, Houston, Texas 77030.

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities.
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http://dx.doi.org/10.1210/me.2016-1095DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965847PMC
August 2016

Research Resources for Nuclear Receptor Signaling Pathways.

Authors:
Neil J McKenna

Mol Pharmacol 2016 Aug 23;90(2):153-9. Epub 2016 May 23.

Department of Molecular and Cellular Biology and Nuclear Receptor Signaling Atlas Bioinformatics Resource, Baylor College of Medicine, Houston, Texas

Nuclear receptor (NR) signaling pathways impact cellular function in a broad variety of tissues in both normal physiology and disease states. The complex tissue-specific biology of these pathways is an enduring impediment to the development of clinical NR small-molecule modulators that combine therapeutically desirable effects in specific target tissues with suppression of off-target effects in other tissues. Supporting the important primary research in this area is a variety of web-based resources that assist researchers in gaining an appreciation of the molecular determinants of the pharmacology of a NR pathway in a given tissue. In this study, selected representative examples of these tools are reviewed, along with discussions on how current and future generations of tools might optimally adapt to the future of NR signaling research.
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http://dx.doi.org/10.1124/mol.116.103713DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959089PMC
August 2016

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

PLoS One 2015 1;10(9):e0135615. Epub 2015 Sep 1.

Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, Texas, United States of America; Nuclear Receptor Signaling Atlas (NURSA) Informatics Hub.

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0135615PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4556694PMC
May 2016

Nuclear Receptor Signaling: a home for nuclear receptor and coregulator signaling research.

Nucl Recept Signal 2014 15;12:e006. Epub 2014 Dec 15.

Nuclear Receptor Signaling Atlas (NJM, RME, BWO) and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030 (NJM, BWO), and Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037 (RME).

The field of nuclear receptor and coregulator signaling has grown into one of the most active and interdisciplinary in eukaryotic biology. Papers in this field are spread widely across a vast number of journals, which complicates the task of investigators in keeping current with the literature in the field. In 2003, we launched Nuclear Receptor Signaling as an Open Access reviews, perspectives and methods journal for the nuclear receptor signaling field. Building on its success and impact on the community, we have added primary research and dataset articles to this list of article categories, and we now announce the re-launch of the journal this month. Here we will summarize the rationale that informed the creation and expansion of the journal, and discuss the possibilities for its future development.
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http://dx.doi.org/10.1621/nrs.12006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4303009PMC
June 2015

Androgen receptor agonism promotes an osteogenic gene program in preadipocytes.

Biochem Biophys Res Commun 2013 May 6;434(2):357-62. Epub 2013 Apr 6.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.

Androgens regulate body composition by interacting with the androgen receptor (AR) to control gene expression in a tissue-specific manner. To identify novel regulatory roles for AR in preadipocytes, we created a 3T3-L1 cell line stably expressing human AR. We found AR expression is required for androgen-mediated inhibition of 3T3-L1 adipogenesis. This inhibition is characterized by decreased lipid accumulation, reduced expression of adipogenic genes, and induction of genes associated with osteoblast differentiation. Collectively, our results suggest androgens promote an osteogenic gene program at the expense of adipocyte differentiation.
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http://dx.doi.org/10.1016/j.bbrc.2013.03.078DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763992PMC
May 2013

Feed-forward inhibition of androgen receptor activity by glucocorticoid action in human adipocytes.

Chem Biol 2012 Sep;19(9):1126-41

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.

We compared transcriptomes of terminally differentiated mouse 3T3-L1 and human adipocytes to identify cell-specific differences. Gene expression and high content analysis (HCA) data identified the androgen receptor (AR) as both expressed and functional, exclusively during early human adipocyte differentiation. The AR agonist dihydrotestosterone (DHT) inhibited human adipocyte maturation by downregulation of adipocyte marker genes, but not in 3T3-L1. It is interesting that AR induction corresponded with dexamethasone activation of the glucocorticoid receptor (GR); however, when exposed to the differentiation cocktail required for adipocyte maturation, AR adopted an antagonist conformation and was transcriptionally repressed. To further explore effectors within the cocktail, we applied an image-based support vector machine (SVM) classification scheme to show that adipocyte differentiation components inhibit AR action. The results demonstrate human adipocyte differentiation, via GR activation, upregulates AR but also inhibits AR transcriptional activity.
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http://dx.doi.org/10.1016/j.chembiol.2012.07.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4259876PMC
September 2012

Activation of NF-κB protein prevents the transition from juvenile ovary to testis and promotes ovarian development in zebrafish.

J Biol Chem 2012 Nov 17;287(45):37926-38. Epub 2012 Sep 17.

Department of Biology, Örebro Life Science Center, School of Science and Technology, Örebro University, SE-701 82 Örebro, Sweden.

Testis differentiation in zebrafish involves juvenile ovary to testis transformation initiated by an apoptotic wave. The molecular regulation of this transformation process is not fully understood. NF-κB is activated at an early stage of development and has been shown to interact with steroidogenic factor-1 in mammals, leading to the suppression of anti-Müllerian hormone (Amh) gene expression. Because steroidogenic factor-1 and Amh are important for proper testis development, NF-κB-mediated induction of anti-apoptotic genes could, therefore, also play a role in zebrafish gonad differentiation. The aim of this study was to examine the potential role of NF-κB in zebrafish gonad differentiation. Exposure of juvenile zebrafish to heat-killed Escherichia coli activated the NF-κB pathways and resulted in an increased ratio of females from 30 to 85%. Microarray and quantitative real-time-PCR analysis of gonads showed elevated expression of NF-κB-regulated genes. To confirm the involvement of NF-κB-induced anti-apoptotic effects, zebrafish were treated with sodium deoxycholate, a known inducer of NF-κB or NF-κB activation inhibitor (NAI). Sodium deoxycholate treatment mimicked the effect of heat-killed bacteria and resulted in an increased proportion of females from 25 to 45%, whereas the inhibition of NF-κB using NAI resulted in a decrease in females from 45 to 20%. This study provides proof for an essential role of NF-κB in gonadal differentiation of zebrafish and represents an important step toward the complete understanding of the complicated process of sex differentiation in this species and possibly other cyprinid teleosts as well.
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http://dx.doi.org/10.1074/jbc.M112.386284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3488064PMC
November 2012

Minireview: progress and challenges in proteomics data management, sharing, and integration.

Mol Endocrinol 2012 Oct 17;26(10):1660-74. Epub 2012 Aug 17.

Department of Medicine, Hematology and Oncology, Baylor College of Medicine, 1 Baylor Plaza MS-BCM305, Houston, Texas 77030, USA.

The proteome represents the identity, expression levels, interacting partners, and posttranslational modifications of proteins expressed within any given cell. Proteomic studies aim to census the quantitative and qualitative factors regulating the biological relationships of proteins acting in concert as functional cellular networks. In the field of endocrinology, proteomics has been of considerable value in determining the function and mechanism of action of endocrine signaling molecules in the cell membrane, cytoplasm, and nucleus and for the discovery of proteins as candidates for clinical biomarkers. The volume of data that can be generated by proteomics methodologies, up to gigabytes of data within a few hours, brings with it its own logistical hurdles and presents significant challenges to realizing the full potential of these datasets. In this minireview, we describe selected current proteomics methodologies and their application in basic and translational endocrinology before focusing on mass spectrometry as a model for current progress and challenges in data analysis, management, sharing, and integration.
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http://dx.doi.org/10.1210/me.2012-1180DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458223PMC
October 2012

Transcriptomine, a web resource for nuclear receptor signaling transcriptomes.

Physiol Genomics 2012 Sep 10;44(17):853-63. Epub 2012 Jul 10.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.

The nuclear receptor (NR) superfamily of ligand-regulated transcription factors directs ligand- and tissue-specific transcriptomes in myriad developmental, metabolic, immunological, and reproductive processes. The NR signaling field has generated a wealth of genome-wide expression data points, but due to deficits in their accessibility, annotation, and integration, the full potential of these studies has not yet been realized. We searched public gene expression databases and MEDLINE for global transcriptomic datasets relevant to NRs, their ligands, and coregulators. We carried out extensive, deep reannotation of the datasets using controlled vocabularies for RNA Source and regulating molecule and resolved disparate gene identifiers to official gene symbols to facilitate comparison of fold changes and their significance across multiple datasets. We assembled these data points into a database, Transcriptomine (http://www.nursa.org/transcriptomine), that allows for multiple, menu-driven querying strategies of this transcriptomic "superdataset," including single and multiple genes, Gene Ontology terms, disease terms, and uploaded custom gene lists. Experimental variables such as regulating molecule, RNA Source, as well as fold-change and P value cutoff values can be modified, and full data records can be either browsed or downloaded for downstream analysis. We demonstrate the utility of Transcriptomine as a hypothesis generation and validation tool using in silico and experimental use cases. Our resource empowers users to instantly and routinely mine the collective biology of millions of previously disparate transcriptomic data points. By incorporating future transcriptome-wide datasets in the NR signaling field, we anticipate Transcriptomine developing into a powerful resource for the NR- and other signal transduction research communities.
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http://dx.doi.org/10.1152/physiolgenomics.00033.2012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3472459PMC
September 2012

Research resource: dkCOIN, the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) consortium interconnectivity network: a pilot program to aggregate research resources generated by multiple research consortia.

Mol Endocrinol 2012 Oct 25;26(10):1675-81. Epub 2012 Jun 25.

Ph.D, Vanderbilt Center Stem for Cell Biology, Vanderbilt University Medical Center, 1207 17th Avenue South, Suite 200, Nashville, Tennessee 37203, USA.

The National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) supports multiple basic science consortia that generate high-content datasets, reagent resources, and methodologies, in the fields of kidney, urology, hematology, digestive, and endocrine diseases, as well as metabolic diseases such as diabetes and obesity. These currently include the Beta Cell Biology Consortium, the Nuclear Receptor Signaling Atlas, the Diabetic Complications Consortium, and the Mouse Metabolic Phenotyping Centers. Recognizing the synergy that would accrue from aggregating information generated and curated by these initiatives in a contiguous informatics network, we created the NIDDK Consortium Interconnectivity Network (dkCOIN; www.dkcoin.org). The goal of this pilot project, organized by the NIDDK, was to establish a single point of access to a toolkit of interconnected resources (datasets, reagents, and protocols) generated from individual consortia that could be readily accessed by biologists of diverse backgrounds and research interests. During the pilot phase of this activity dkCOIN collected nearly 2000 consortium-curated resources, including datasets (functional genomics) and reagents (mouse strains, antibodies, and adenoviral constructs) and built nearly 3000 resource-to-resource connections, thereby demonstrating the feasibility of further extending this database in the future. Thus, dkCOIN promises to be a useful informatics solution for rapidly identifying useful resources generated by participating research consortia.
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http://dx.doi.org/10.1210/me.2012-1077DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458218PMC
October 2012

EMBO Retinoids 2011: Mechanisms, biology and pathology of signaling by retinoic acid and retinoic acid receptors.

Authors:
Neil J McKenna

Nucl Recept Signal 2012 27;10:e003. Epub 2012 Feb 27.

Department of Molecular and Cellular Biology and Nuclear Receptor Signaling Atlas (NURSA), Baylor College of Medicine, Houston, Texas, USA.

Retinoic acid (RA) is one of the principal active metabolites of vitamin A (retinol) which mediates a spectrum of critical physiological and developmental processes. Transcriptional regulation by RA is mediated primarily by members of the retinoic acid receptor (RAR) subfamily of the nuclear receptor (NR) superfamily of transcription factors. NRs bind specific genomic DNA sequence motifs and engage coregulators and components of the basal transcription machinery to effect transcriptional regulation at target gene promoters. Disruption of signaling by retinoic acid is thought to underlie the etiology of a number of inflammatory and neoplastic diseases including breast cancer and haematological malignancies. A meeting of international researchers in retinoid signaling was convened in Strasbourg in September 2011 under the auspices of the European Molecular Biology Organization (EMBO). Retinoids 2011 encompassed myriad mechanistic, biological and pathological aspects of these hormones and their cognate receptors, as well as setting these advances in the context of wider current questions on signaling by members of the NR superfamily.
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http://dx.doi.org/10.1621/nrs.10003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3309077PMC
May 2012

Combined deletion of Fxr and Shp in mice induces Cyp17a1 and results in juvenile onset cholestasis.

J Clin Invest 2011 Jan 1;121(1):86-95. Epub 2010 Dec 1.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.

Bile acid homeostasis is tightly regulated via a feedback loop operated by the nuclear receptors farnesoid X receptor (FXR) and small heterodimer partner (SHP). Contrary to current models, which place FXR upstream of SHP in a linear regulatory pathway, here we show that the phenotypic consequences in mice of the combined loss of both receptors are much more severe than the relatively modest impact of the loss of either Fxr or Shp alone. Fxr-/-Shp-/- mice exhibited cholestasis and liver injury as early as 3 weeks of age, and this was linked to the dysregulation of bile acid homeostatic genes, particularly cytochrome P450, family 7, subfamily a, polypeptide 1 (Cyp7a1). In addition, double-knockout mice showed misregulation of genes in the C21 steroid biosynthesis pathway, with strong induction of cytochrome P450, family 17, subfamily a, polypeptide 1 (Cyp17a1), resulting in elevated serum levels of its enzymatic product 17-hydroxyprogesterone (17-OHP). Treatment of WT mice with 17-OHP was sufficient to induce liver injury that reproduced many of the histopathological features observed in the double-knockout mice. Therefore, our data indicate a pathologic role for increased production of 17-hydroxy steroid metabolites in liver injury and suggest that Fxr-/-Shp-/- mice could provide a model for juvenile onset cholestasis.
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http://dx.doi.org/10.1172/JCI42846DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3007143PMC
January 2011

Discovery-driven research and bioinformatics in nuclear receptor and coregulator signaling.

Authors:
Neil J McKenna

Biochim Biophys Acta 2011 Aug 26;1812(8):808-17. Epub 2010 Oct 26.

Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.

Nuclear receptors (NRs) are a superfamily of ligand-regulated transcription factors that interact with coregulators and other transcription factors to direct tissue-specific programs of gene expression. Recent years have witnessed a rapid acceleration of the output of high-content data platforms in this field, generating discovery-driven datasets that have collectively described: the organization of the NR superfamily (phylogenomics); the expression patterns of NRs, coregulators and their target genes (transcriptomics); ligand- and tissue-specific functional NR and coregulator sites in DNA (cistromics); the organization of nuclear receptors and coregulators into higher order complexes (proteomics); and their downstream effects on homeostasis and metabolism (metabolomics). Significant bioinformatics challenges lie ahead both in the integration of this information into meaningful models of NR and coregulator biology, as well as in the archiving and communication of datasets to the global nuclear receptor signaling community. While holding great promise for the field, the ascendancy of discovery-driven research in this field brings with it a collective responsibility for researchers, publishers and funding agencies alike to ensure the effective archiving and management of these data. This review will discuss factors lying behind the increasing impact of discovery-driven research, examples of high-content datasets and their bioinformatic analysis, as well as a summary of currently curated web resources in this field. This article is part of a Special Issue entitled: Translating nuclear receptors from health to disease.
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http://dx.doi.org/10.1016/j.bbadis.2010.10.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3609546PMC
August 2011

SnapShot: NR coregulators.

Cell 2010 Oct;143(1):172-172.e1

Baylor College of Medicine, Houston, TX 77030, USA.

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http://dx.doi.org/10.1016/j.cell.2010.09.032DOI Listing
October 2010

SnapShot: Nuclear receptors II.

Cell 2010 Sep;142(6):986.e1

Baylor College of Medicine, Houston, TX 77030, USA.

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http://dx.doi.org/10.1016/j.cell.2010.08.041DOI Listing
September 2010

SnapShot: Nuclear receptors I.

Cell 2010 Sep;142(5):822-822.e1

Baylor College of Medicine, Houston, TX 77030, USA.

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http://dx.doi.org/10.1016/j.cell.2010.08.026DOI Listing
September 2010

Research resource: Tissue-specific transcriptomics and cistromics of nuclear receptor signaling: a web research resource.

Mol Endocrinol 2010 Oct 4;24(10):2065-9. Epub 2010 Aug 4.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.

Nuclear receptors (NRs) are ligand-regulated transcription factors that recruit coregulators and other transcription factors to gene promoters to effect regulation of tissue-specific transcriptomes. The prodigious rate at which the NR signaling field has generated high content gene expression and, more recently, genome-wide location analysis datasets has not been matched by a committed effort to archiving this information for routine access by bench and clinical scientists. As a first step towards this goal, we searched the MEDLINE database for studies, which referenced either expression microarray and/or genome-wide location analysis datasets in which a NR or NR ligand was an experimental variable. A total of 1122 studies encompassing 325 unique organs, tissues, primary cells, and cell lines, 35 NRs, and 91 NR ligands were retrieved and annotated. The data were incorporated into a new section of the Nuclear Receptor Signaling Atlas Molecule Pages, Transcriptomics and Cistromics, for which we designed an intuitive, freely accessible user interface to browse the studies. Each study links to an abstract, the MEDLINE record, and, where available, Gene Expression Omnibus and ArrayExpress records. The resource will be updated on a regular basis to provide a current and comprehensive entrez into the sum of transcriptomic and cistromic research in this field.
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http://dx.doi.org/10.1210/me.2010-0216DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2954640PMC
October 2010

Minireview: Evolution of NURSA, the Nuclear Receptor Signaling Atlas.

Mol Endocrinol 2009 Jun 7;23(6):740-6. Epub 2009 May 7.

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.

Nuclear receptors and coregulators are multifaceted players in normal metabolic and homeostatic processes in addition to a variety of disease states including cancer, inflammation, diabetes, obesity, and atherosclerosis. Over the past 7 yr, the Nuclear Receptor Signaling Atlas (NURSA) research consortium has worked toward establishing a discovery-driven platform designed to address key questions concerning the expression, organization, and function of these molecules in a variety of experimental model systems. By applying powerful technologies such as quantitative PCR, high-throughput mass spectrometry, and embryonic stem cell manipulation, we are pursuing these questions in a series of transcriptomics-, proteomics-, and metabolomics-based research projects and resources. The consortium's web site (www.nursa.org) integrates NURSA datasets and existing public datasets with the ultimate goal of furnishing the bench scientist with a comprehensive framework for hypothesis generation, modeling, and testing. We place a strong emphasis on community input into the development of this resource and to this end have published datasets from academic and industrial laboratories, established strategic alliances with Endocrine Society journals, and are developing tools to allow web site users to act as data curators. With the ongoing support of the nuclear receptor and coregulator signaling communities, we believe that NURSA can make a lasting contribution to research in this dynamic field.
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http://dx.doi.org/10.1210/me.2009-0135DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691684PMC
June 2009

Re-expression of GATA2 cooperates with peroxisome proliferator-activated receptor-gamma depletion to revert the adipocyte phenotype.

J Biol Chem 2009 Apr 9;284(14):9458-64. Epub 2009 Jan 9.

Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Univ. of Pennsylvania School of Medicine, 700 CRB, 415 Curie Blvd., Philadelphia, PA 19104-6149, USA.

Nuclear peroxisome proliferator-activated receptor-gamma (PPARgamma) is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here, we report that knockdown of PPARgamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes to preadipocyte levels. Consistently, down-regulated but not up-regulated genes showed strong enrichment of PPARgamma binding. Surprisingly, not all adipocyte genes were reversed, and the adipocyte morphology was maintained for an extended period after PPARgamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPARgamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation and whose levels remain low after PPARgamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPARgamma depletion and impaired adipocyte functionality with a more preadipocyte-like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had a similar effect on adipogenic gene expression. These results suggest that PPARgamma-independent down-regulation of GATA2 prevents reversion of mature adipocytes after PPARgamma depletion.
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http://dx.doi.org/10.1074/jbc.M809498200DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2666598PMC
April 2009