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Valle-Maldonado MI, Patiño-Medina JA, Pérez-Arques C, Reyes-Mares NY, Jácome-Galarza IE, Ortíz-Alvarado R, Vellanki S, Ramírez-Díaz MI, Lee SC, Garre V, Meza-Carmen V. The heterotrimeric G-protein beta subunit Gpb1 controls hyphal growth under low oxygen conditions through the protein kinase A pathway and is essential for virulence in the fungus Mucor circinelloides. Cell Microbiol 2020; 22:e13236. [PMID: 32562333 DOI: 10.1111/cmi.13236] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 05/24/2020] [Accepted: 06/09/2020] [Indexed: 12/13/2022]
Abstract
Mucor circinelloides, a dimorphic opportunistic pathogen, expresses three heterotrimeric G-protein beta subunits (Gpb1, Gpb2 and Gpb3). The Gpb1-encoding gene is up-regulated during mycelial growth compared with that in the spore or yeast stage. gpb1 deletion mutation analysis revealed its relevance for an adequate development during the dimorphic transition and for hyphal growth under low oxygen concentrations. Infection assays in mice indicated a phenotype with considerably reduced virulence and tissue invasiveness in the deletion mutants (Δgpb1) and decreased host inflammatory response. This finding could be attributed to the reduced filamentous growth in animal tissues compared with that of the wild-type strain. Mutation in a regulatory subunit of cAMP-dependent protein kinase A (PKA) subunit (PkaR1) resulted in similar phenotypes to Δgpb1. The defects exhibited by the Δgpb1 strain were genetically suppressed by pkaR1 overexpression, indicating that the PKA pathway is controlled by Gpb1 in M. circinelloides. Moreover, during growth under low oxygen levels, cAMP levels were much higher in the Δgpb1 than in the wild-type strain, but similar to those in the ΔpkaR1 strain. These findings reveal that M. circinelloides possesses a signal transduction pathway through which the Gpb1 heterotrimeric G subunit and PkaR1 control mycelial growth in response to low oxygen levels.
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Affiliation(s)
- Marco Iván Valle-Maldonado
- Instituto de Investigaciones Químico Biológicas, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Mexico
| | - José Alberto Patiño-Medina
- Instituto de Investigaciones Químico Biológicas, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Mexico
| | - Carlos Pérez-Arques
- Departamento de Genética y Microbiología, Facultad de Biología, Universidad de Murcia, Murcia, Spain
| | - Nancy Yadira Reyes-Mares
- Instituto de Investigaciones Químico Biológicas, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Mexico
| | | | - Rafael Ortíz-Alvarado
- Facultad de Quimico Farmacobiología, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico
| | - Sandeep Vellanki
- South Texas Center for Emerging Infectious Diseases (STCEID), Department of Biology, The University of Texas at San Antonio, San Antonio, Texas, USA
| | - Martha Isela Ramírez-Díaz
- Instituto de Investigaciones Químico Biológicas, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Mexico
| | - Soo Chan Lee
- South Texas Center for Emerging Infectious Diseases (STCEID), Department of Biology, The University of Texas at San Antonio, San Antonio, Texas, USA
| | - Victoriano Garre
- Departamento de Genética y Microbiología, Facultad de Biología, Universidad de Murcia, Murcia, Spain
| | - Víctor Meza-Carmen
- Instituto de Investigaciones Químico Biológicas, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Mexico
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2
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Dumbo JC, Dos Santos QM, Avenant-Oldewage A. Morphological and molecular characterization of Glossidium pedatum Looss, 1899 and Orientocreadium batrachoides Tubangui, 1931 from sharptooth catfish, Clarias gariepinus (Burchell, 1822). AFRICAN ZOOLOGY 2019. [DOI: 10.1080/15627020.2019.1595143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- José Chissiua Dumbo
- Department of Zoology, University of Johannesburg, Johannesburg, South Africa
- Department of Biological Science, Science Faculty, Eduardo Mondlane University, Maputo, Mozambique
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3
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Dumbo JC, Dos Santos QM, Avenant-Oldewage A. Masenia nkomatiensis n. sp. (Digenea: Cephalogonimidae) from Clarias gariepinus (Burchell) (Clariidae) in Incomati Basin, Mozambique. Syst Parasitol 2019; 96:311-326. [PMID: 30903447 DOI: 10.1007/s11230-019-09848-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 02/02/2019] [Indexed: 11/27/2022]
Abstract
A new species of Masenia Chatterji, 1933 is described based on material from the intestine of Clarias gariepinus (Burchell) in the Incomati River, Mozambique. The combination of morphological characteristics and analysis of 18S and 28S rDNA sequences delineated the specimens found in the present study as a distinct species. The new form is distinguished from other Masenia spp. in having a large reniform seminal receptacle, a cirrus-sac ending anterior to the ventral sucker, intestinal caeca extending into the hindbody to the level of the posterior testis, and the vitelline fields extending anteriorly to the ventral sucker and posteriorly to the middle of the ovary. Notably, the new form is the only record of African species having a sac-shaped excretory vesicle. Analysis of 28S rDNA sequence data supported its placement in the Cephalogonimidae Looss, 1899. 18S analyses also supported its placement in this family but showed it was not closely related to Masenia bangweulensis (Beverley-Burton, 1962), the sole other African species for which genetic data is currently accessible. The total pairwise differences for 18S and 28S sequences showed the new form differing from other cephalogonimids. Thus, both morphological and genetic characteristics indicate that the present form represents a distinct species, here described as Masenia nkomatiensis n. sp. An updated key to African Masenia spp., now five, is provided.
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Affiliation(s)
- José Chissiua Dumbo
- Department of Zoology, University of Johannesburg, Johannesburg, Gauteng, South Africa
- Department of Biological Science, Eduardo Mondlane University, Maputo, Mozambique
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4
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Igeh PC, Dos Santos QM, Avenant-Oldewage A. Redescription of Cichlidogyrus philander (Monogenea, Ancyrocephalidae) using scanning electron microscopy (SEM) and molecular analysis. ACTA ACUST UNITED AC 2017; 24:49. [PMID: 29194034 PMCID: PMC5711379 DOI: 10.1051/parasite/2017046] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 11/02/2017] [Indexed: 11/14/2022]
Abstract
The sclerotized structures of monogeneans have traditionally been studied by light microscopy and different staining techniques. Recently, enzymatic digestion followed by scanning electron microscopy (SEM) has enabled the examination of structural details not visible with light microscopy. In order to obtain better, and more accurate, morphological information on sclerotized structures not affected by mounting medium or cover slip pressure, the sclerites of Cichlidogyrus philander Douëllou, 1993 (Monogenea, Ancyrocephalidae), collected from Pseudocrenilabrus philander (Weber, 1897), were redescribed using SEM. Parasites were collected from Padda Dam, Gauteng, South Africa and soft tissue was digested to release the sclerotized structures. The digested tissue also provided sufficient genetic material for molecular characterization of this species. Cichlidogyrus philander is characterised by a penis with a sharp, curved, lateral termination, an accessory piece with a hook-like extremity that may appear forked terminally, and lack of a visible vagina. The transverse bars have concave and convex surfaces with ribs on the concave surface. The dorsal bar bears fenestrations at the base of the auricles and the ventral and dorsal gripi are dissimilar. Furthermore, the large first pair of uncinuli shows lateral wings on the left side of the base. On top of this wing, a ball-like structure with a small fenestration is visible. Genetic characters derived from the 28S rDNA, the COI mitochondrial DNA and ITS1 rDNA regions distinguish C. philander from all other Cichlidogyrus sequenced species.
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Affiliation(s)
- Patience C Igeh
- Department of Zoology, University of Johannesburg, PO Box 524, Auckland Park 2006, Johannesburg, South Africa - Department of Microbiology, Plateau State University, PO Box 2012, Jos, Nigeria
| | - Quinton M Dos Santos
- Department of Zoology, University of Johannesburg, PO Box 524, Auckland Park 2006, Johannesburg, South Africa
| | - Annemariè Avenant-Oldewage
- Department of Zoology, University of Johannesburg, PO Box 524, Auckland Park 2006, Johannesburg, South Africa
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5
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Souza TM, van den Beucken T, Kleinjans JCS, Jennen DGJ. Inferring transcription factor activity from microarray data reveals novel targets for toxicological investigations. Toxicology 2017; 389:101-107. [PMID: 28743512 DOI: 10.1016/j.tox.2017.07.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 07/12/2017] [Accepted: 07/13/2017] [Indexed: 01/09/2023]
Abstract
Transcription factors (TFs) are important modulators of the inducible portion of the transcriptome, and therefore relevant in the context of exposure to exogenous compounds. Current approaches to predict the activity of TFs in biological systems are usually restricted to a few entities at a time due to low-throughput techniques targeting a limited fraction of annotated human TFs. Therefore, high-throughput alternatives may help to identify new targets of mechanistic and predictive value in toxicological investigations. In this study, we inferred the activity multiple TFs using publicly available microarray data from primary human hepatocytes exposed to hundreds of chemicals and evaluated these molecular profiles using multiple correspondence analysis. Our results demonstrate that the lowest dose and latest exposure time (24h) in a subset of chemicals generates a signature indicative of carcinogenicity possibly due to DNA-damaging properties. Furthermore, profiles from the earliest exposure time (2h) and highest dose creates clusters of chemicals implicated in the development of diverse forms of drug-induced liver injury (DILI). Both approaches yielded a number of TFs with similar activity across groups of chemicals, including TFs known in toxicological responses such as AhR, NFE2L2 (Nrf2), NF-κB and PPARG. FOXM1, IRF1 and E2F4 were some of the TFs identified that may be relevant in genotoxic carcinogenesis. SMADs (SMAD1, SMAD2, SMAD5) and KLF5 were identified as some of potentially new TFs whose inferred activities were linked to acute and progressive outcomes in DILI. In conclusion this study offers a novel mechanistic approach targeting TF activity during chemical exposure.
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Affiliation(s)
- T M Souza
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, 6229 ER, The Netherlands.
| | - T van den Beucken
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, 6229 ER, The Netherlands
| | - J C S Kleinjans
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, 6229 ER, The Netherlands
| | - D G J Jennen
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, 6229 ER, The Netherlands
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Chen X, Gao C, Guo L, Hu G, Luo Q, Liu J, Nielsen J, Chen J, Liu L. DCEO Biotechnology: Tools To Design, Construct, Evaluate, and Optimize the Metabolic Pathway for Biosynthesis of Chemicals. Chem Rev 2017; 118:4-72. [DOI: 10.1021/acs.chemrev.6b00804] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Xiulai Chen
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Cong Gao
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Liang Guo
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Guipeng Hu
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Qiuling Luo
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Jia Liu
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Jens Nielsen
- Department
of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg SE-412 96, Sweden
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK2800 Lyngby, Denmark
| | - Jian Chen
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Liming Liu
- State
Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- Department
of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg SE-412 96, Sweden
- Key
Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
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7
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Hobbs ET, Pereira T, O’Neill PK, Erill I. A Bayesian inference method for the analysis of transcriptional regulatory networks in metagenomic data. Algorithms Mol Biol 2016; 11:19. [PMID: 27398089 PMCID: PMC4938975 DOI: 10.1186/s13015-016-0082-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 06/30/2016] [Indexed: 11/13/2022] Open
Abstract
Background Metagenomics enables the analysis of bacterial population composition and the study of emergent population features, such as shared metabolic pathways. Recently, we have shown that metagenomics datasets can be leveraged to characterize population-wide transcriptional regulatory networks, or meta-regulons, providing insights into how bacterial populations respond collectively to specific triggers. Here we formalize a Bayesian inference framework to analyze the composition of transcriptional regulatory networks in metagenomes by determining the probability of regulation of orthologous gene sequences. We assess the performance of this approach on synthetic datasets and we validate it by analyzing the copper-homeostasis network of Firmicutes species in the human gut microbiome. Results Assessment on synthetic datasets shows that our method provides a robust and interpretable metric for assessing putative regulation by a transcription factor on sets of promoter sequences mapping to an orthologous gene cluster. The inference framework integrates the regulatory contribution of secondary sites and can discern false positives arising from multiple instances of a clonal sequence. Posterior probabilities for orthologous gene clusters decline sharply when less than 20 % of mapped promoters have binding sites, but we introduce a sensitivity adjustment procedure to speed up computation that enhances regulation assessment in heterogeneous ortholog clusters. Analysis of the copper-homeostasis regulon governed by CsoR in the human gut microbiome Firmicutes reveals that CsoR controls itself and copper-translocating P-type ATPases, but not CopZ-type copper chaperones. Our analysis also indicates that CsoR frequently targets promoters with dual CsoR-binding sites, suggesting that it exploits higher-order binding conformations to fine-tune its activity. Conclusions We introduce and validate a method for the analysis of transcriptional regulatory networks from metagenomic data that enables inference of meta-regulons in a systematic and interpretable way. Validation of this method on the CsoR meta-regulon of gut microbiome Firmicutes illustrates the usefulness of the approach, revealing novel properties of the copper-homeostasis network in poorly characterized bacterial species and putting forward evidence of new mechanisms of DNA binding for this transcriptional regulator. Our approach will enable the comparative analysis of regulatory networks across metagenomes, yielding novel insights into the evolution of transcriptional regulatory networks. Electronic supplementary material The online version of this article (doi:10.1186/s13015-016-0082-8) contains supplementary material, which is available to authorized users.
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8
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Mahajan G, Mande SC. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach. PLoS One 2015; 10:e0142147. [PMID: 26562430 PMCID: PMC4642966 DOI: 10.1371/journal.pone.0142147] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 10/19/2015] [Indexed: 11/19/2022] Open
Abstract
High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.
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9
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Ortega AD, Quereda JJ, Pucciarelli MG, García-del Portillo F. Non-coding RNA regulation in pathogenic bacteria located inside eukaryotic cells. Front Cell Infect Microbiol 2014; 4:162. [PMID: 25429360 PMCID: PMC4228915 DOI: 10.3389/fcimb.2014.00162] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2014] [Accepted: 10/20/2014] [Indexed: 01/06/2023] Open
Abstract
Intracellular bacterial pathogens have evolved distinct lifestyles inside eukaryotic cells. Some pathogens coexist with the infected cell in an obligate intracellular state, whereas others transit between the extracellular and intracellular environment. Adaptation to these intracellular lifestyles is regulated in both space and time. Non-coding small RNAs (sRNAs) are post-transcriptional regulatory molecules that fine-tune important processes in bacterial physiology including cell envelope architecture, intermediate metabolism, bacterial communication, biofilm formation, and virulence. Recent studies have shown production of defined sRNA species by intracellular bacteria located inside eukaryotic cells. The molecules targeted by these sRNAs and their expression dynamics along the intracellular infection cycle remain, however, poorly characterized. Technical difficulties linked to the isolation of “intact” intracellular bacteria from infected host cells might explain why sRNA regulation in these specialized pathogens is still a largely unexplored field. Transition from the extracellular to the intracellular lifestyle provides an ideal scenario in which regulatory sRNAs are intended to participate; so much work must be done in this direction. This review focuses on sRNAs expressed by intracellular bacterial pathogens during the infection of eukaryotic cells, strategies used with these pathogens to identify sRNAs required for virulence, and the experimental technical challenges associated to this type of studies. We also discuss varied techniques for their potential application to study RNA regulation in intracellular bacterial infections.
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Affiliation(s)
- Alvaro D Ortega
- Centro Nacional de Biotecnología - Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid, Spain
| | - Juan J Quereda
- Centro Nacional de Biotecnología - Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid, Spain
| | - M Graciela Pucciarelli
- Centro Nacional de Biotecnología - Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid, Spain ; Departamento de Biología Molecular, Universidad Autónoma de Madrid, Centro de Biología Molecular 'Severo Ochoa' (CBMSO-CSIC) Madrid, Spain
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10
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Primate-specific endogenous retrovirus-driven transcription defines naive-like stem cells. Nature 2014; 516:405-9. [PMID: 25317556 DOI: 10.1038/nature13804] [Citation(s) in RCA: 304] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Accepted: 08/28/2014] [Indexed: 01/21/2023]
Abstract
Naive embryonic stem cells hold great promise for research and therapeutics as they have broad and robust developmental potential. While such cells are readily derived from mouse blastocysts it has not been possible to isolate human equivalents easily, although human naive-like cells have been artificially generated (rather than extracted) by coercion of human primed embryonic stem cells by modifying culture conditions or through transgenic modification. Here we show that a sub-population within cultures of human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs) manifests key properties of naive state cells. These naive-like cells can be genetically tagged, and are associated with elevated transcription of HERVH, a primate-specific endogenous retrovirus. HERVH elements provide functional binding sites for a combination of naive pluripotency transcription factors, including LBP9, recently recognized as relevant to naivety in mice. LBP9-HERVH drives hESC-specific alternative and chimaeric transcripts, including pluripotency-modulating long non-coding RNAs. Disruption of LBP9, HERVH and HERVH-derived transcripts compromises self-renewal. These observations define HERVH expression as a hallmark of naive-like hESCs, and establish novel primate-specific transcriptional circuitry regulating pluripotency.
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11
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Liu G, Marras A, Nielsen J. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network. QUANTITATIVE BIOLOGY 2014. [DOI: 10.1007/s40484-014-0027-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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12
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Bouhifd M, Hogberg HT, Kleensang A, Maertens A, Zhao L, Hartung T. Mapping the human toxome by systems toxicology. Basic Clin Pharmacol Toxicol 2014; 115:24-31. [PMID: 24443875 DOI: 10.1111/bcpt.12198] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2013] [Accepted: 01/03/2014] [Indexed: 12/26/2022]
Abstract
Toxicity testing typically involves studying adverse health outcomes in animals subjected to high doses of toxicants with subsequent extrapolation to expected human responses at lower doses. The low-throughput of current toxicity testing approaches (which are largely the same for industrial chemicals, pesticides and drugs) has led to a backlog of more than 80,000 chemicals to which human beings are potentially exposed whose potential toxicity remains largely unknown. Employing new testing strategies that employ the use of predictive, high-throughput cell-based assays (of human origin) to evaluate perturbations in key pathways, referred as pathways of toxicity, and to conduct targeted testing against those pathways, we can begin to greatly accelerate our ability to test the vast 'storehouses' of chemical compounds using a rational, risk-based approach to chemical prioritization and provide test results that are more predictive of human toxicity than current methods. The NIH Transformative Research Grant project Mapping the Human Toxome by Systems Toxicology aims at developing the tools for pathway mapping, annotation and validation as well as the respective knowledge base to share this information.
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Affiliation(s)
- Mounir Bouhifd
- Bloomberg School of Public Health, Johns Hopkins University, CAAT, Baltimore, MD, USA
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13
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Perera D, Chacon D, Thoms JAI, Poulos RC, Shlien A, Beck D, Campbell PJ, Pimanda JE, Wong JWH. OncoCis: annotation of cis-regulatory mutations in cancer. Genome Biol 2014; 15:485. [PMID: 25298093 PMCID: PMC4224696 DOI: 10.1186/s13059-014-0485-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2014] [Accepted: 10/01/2014] [Indexed: 01/12/2023] Open
Abstract
Whole genome sequencing has enabled the identification of thousands of somatic mutations within non-coding genomic regions of individual cancer samples. However, identification of mutations that potentially alter gene regulation remains a major challenge. Here we present OncoCis, a new method that enables identification of potential cis-regulatory mutations using cell type-specific genome and epigenome-wide datasets along with matching gene expression data. We demonstrate that the use of cell type-specific information and gene expression can significantly reduce the number of candidate cis-regulatory mutations compared with existing tools designed for the annotation of cis-regulatory SNPs. The OncoCis webserver is freely accessible at https://powcs.med.unsw.edu.au/OncoCis/.
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Affiliation(s)
- Dilmi Perera
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
| | - Diego Chacon
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
| | - Julie AI Thoms
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
| | - Rebecca C Poulos
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
| | - Adam Shlien
- />Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, CB10 1SA UK
| | - Dominik Beck
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
| | - Peter J Campbell
- />Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, CB10 1SA UK
- />Department of Haematology, Addenbrooke’s Hospital, Cambridge, CB2 0QQ UK
| | - John E Pimanda
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
- />Department of Haematology, Prince of Wales Hospital, Sydney, 2031 Australia
| | - Jason WH Wong
- />Prince of Wales Clinical School and Lowy Cancer Research Centre, UNSW Australia, Sydney, 2052 Australia
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14
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Kem MP, Zane HK, Springer SD, Gauglitz JM, Butler A. Amphiphilic siderophore production by oil-associating microbes. Metallomics 2014; 6:1150-5. [DOI: 10.1039/c4mt00047a] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Amphibactin siderophores have been isolated from oil-associatedVibriospp. following the Deepwater Horizon oil spill, and fromAlcanivorax borkumensisSK2.
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Affiliation(s)
- Michelle P. Kem
- Department of Chemistry and Biochemistry
- University of California
- Santa Barbara, USA
| | - Hannah K. Zane
- Department of Chemistry and Biochemistry
- University of California
- Santa Barbara, USA
| | - Stephen D. Springer
- Department of Chemistry and Biochemistry
- University of California
- Santa Barbara, USA
| | - Julia M. Gauglitz
- Department of Chemistry and Biochemistry
- University of California
- Santa Barbara, USA
| | - Alison Butler
- Department of Chemistry and Biochemistry
- University of California
- Santa Barbara, USA
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15
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Finding Transcription Factor Binding Motifs for Coregulated Genes by Combining Sequence Overrepresentation with Cross-Species Conservation. JOURNAL OF PROBABILITY AND STATISTICS 2012. [DOI: 10.1155/2012/830575] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Novel computational methods for finding transcription factor binding motifs have long been sought due to tedious work of experimentally identifying them. However, the current prevailing methods yield a large number of false positive predictions due to the short, variable nature of transcriptional factor binding sites (TFBSs). We proposed here a method that combines sequence overrepresentation and cross-species sequence conservation to detect TFBSs in upstream regions of a given set of coregulated genes. We applied the method to 35S. cerevisiaetranscriptional factors with known DNA binding motifs (with the support of orthologous sequences from genomes ofS. mikatae,S. bayanus, andS. paradoxus), and the proposed method outperformed the single-genome-based motif finding methodsMEMEandAlignACEas well as the multiple-genome-based methodsPHYMEandFootprinterfor the majority of these transcriptional factors. Compared with the prevailing motif finding software, our method has some advantages in finding transcriptional factor binding motifs for potential coregulated genes if the gene upstream sequences of multiple closely related species are available. Although we used yeast genomes to assess our method in this study, it might also be applied to other organisms if suitable related species are available and the upstream sequences of coregulated genes can be obtained for the multiple closely related species.
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Li R, Ackerman WE, Summerfield TL, Yu L, Gulati P, Zhang J, Huang K, Romero R, Kniss DA. Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition. PLoS One 2011; 6:e20560. [PMID: 21655103 PMCID: PMC3107214 DOI: 10.1371/journal.pone.0020560] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2011] [Accepted: 05/05/2011] [Indexed: 11/18/2022] Open
Abstract
A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.
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Affiliation(s)
- Ruth Li
- Division of Maternal-Fetal Medicine and Laboratory of Perinatal Research,
Department of Obstetrics and Gynecology, The Ohio State University, Columbus,
Ohio, United States of America
| | - William E. Ackerman
- Division of Maternal-Fetal Medicine and Laboratory of Perinatal Research,
Department of Obstetrics and Gynecology, The Ohio State University, Columbus,
Ohio, United States of America
| | - Taryn L. Summerfield
- Division of Maternal-Fetal Medicine and Laboratory of Perinatal Research,
Department of Obstetrics and Gynecology, The Ohio State University, Columbus,
Ohio, United States of America
| | - Lianbo Yu
- Center for Biostatistics, The Ohio State University, Columbus, Ohio,
United States of America
| | - Parul Gulati
- Center for Biostatistics, The Ohio State University, Columbus, Ohio,
United States of America
| | - Jie Zhang
- Department of Biomedical Informatics, The Ohio State University,
Columbus, Ohio, United States of America
| | - Kun Huang
- Department of Biomedical Informatics, The Ohio State University,
Columbus, Ohio, United States of America
| | - Roberto Romero
- Perinatology Research Branch, Intramural Division, Eunice Kennedy Shriver
National Institute of Child Health and Human Development, National Institutes of
Health, Department of Health and Human Services, Bethesda, Maryland, United
States of America
- Hutzel Women's Hospital, Detroit, Michigan, United States of
America
| | - Douglas A. Kniss
- Division of Maternal-Fetal Medicine and Laboratory of Perinatal Research,
Department of Obstetrics and Gynecology, The Ohio State University, Columbus,
Ohio, United States of America
- Department of Biomedical Engineering, The Ohio State University,
Columbus, Ohio, United States of America
- * E-mail:
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Hanlon SE, Rizzo JM, Tatomer DC, Lieb JD, Buck MJ. The stress response factors Yap6, Cin5, Phd1, and Skn7 direct targeting of the conserved co-repressor Tup1-Ssn6 in S. cerevisiae. PLoS One 2011; 6:e19060. [PMID: 21552514 PMCID: PMC3084262 DOI: 10.1371/journal.pone.0019060] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2011] [Accepted: 03/23/2011] [Indexed: 11/19/2022] Open
Abstract
Maintaining the proper expression of the transcriptome during development or in response to a changing environment requires a delicate balance between transcriptional regulators with activating and repressing functions. The budding yeast transcriptional co-repressor Tup1-Ssn6 is a model for studying similar repressor complexes in multicellular eukaryotes. Tup1-Ssn6 does not bind DNA directly, but is directed to individual promoters by one or more DNA-binding proteins, referred to as Tup1 recruiters. This functional architecture allows the Tup1-Ssn6 to modulate the expression of genes required for the response to a variety of cellular stresses. To understand the targeting or the Tup1-Ssn6 complex, we determined the genomic distribution of Tup1 and Ssn6 by ChIP-chip. We found that most loci bound by Tup1-Ssn6 could not be explained by co-occupancy with a known recruiting cofactor and that deletion of individual known Tup1 recruiters did not significantly alter the Tup1 binding profile. These observations suggest that new Tup1 recruiting proteins remain to be discovered and that Tup1 recruitment typically depends on multiple recruiting cofactors. To identify new recruiting proteins, we computationally screened for factors with binding patterns similar to the observed Tup1-Ssn6 genomic distribution. Four top candidates, Cin5, Skn7, Phd1, and Yap6, all known to be associated with stress response gene regulation, were experimentally confirmed to physically interact with Tup1 and/or Ssn6. Incorporating these new recruitment cofactors with previously characterized cofactors now explains the majority of Tup1 targeting across the genome, and expands our understanding of the mechanism by which Tup1-Ssn6 is directed to its targets.
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Affiliation(s)
- Sean E. Hanlon
- Department of Biology, Carolina Center for Genome Sciences and the Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jason M. Rizzo
- Department of Biochemistry and the Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, New York, United States of America
| | - Deirdre C. Tatomer
- Department of Biology, Carolina Center for Genome Sciences and the Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jason D. Lieb
- Department of Biology, Carolina Center for Genome Sciences and the Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail: (JDL); (MJB)
| | - Michael J. Buck
- Department of Biochemistry and the Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, New York, United States of America
- * E-mail: (JDL); (MJB)
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Viemann D, Schmolke M, Lueken A, Boergeling Y, Friesenhagen J, Wittkowski H, Ludwig S, Roth J. H5N1 virus activates signaling pathways in human endothelial cells resulting in a specific imbalanced inflammatory response. THE JOURNAL OF IMMUNOLOGY 2010; 186:164-73. [PMID: 21106851 DOI: 10.4049/jimmunol.0904170] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
H5N1 influenza virus infections in humans cause a characteristic systemic inflammatory response syndrome; however, the molecular mechanisms are largely unknown. Endothelial cells (ECs) play a pivotal role in hyperdynamic septic diseases. To unravel specific signaling networks activated by H5N1 we used a genome-wide comparative systems biology approach analyzing gene expression in human ECs infected with three different human and avian influenza strains of high and low pathogenicity. Blocking of specific signaling pathways revealed that H5N1 induces an exceptionally NF-κB-dependent gene response in human endothelia. Additionally, the IFN-driven antiviral program in ECs is shown to be dependent on IFN regulatory factor 3 but significantly impaired upon H5N1 infection compared with low pathogenic influenza virus. As additional modulators of this H5N1-specific imbalanced gene response pattern, we identified HMGA1 as a novel transcription factor specifically responsible for the overwhelming proinflammatory but not antiviral response, whereas NFATC4 was found to regulate transcription of specifically H5N1-induced genes. We describe for the first time, to our knowledge, defined signaling patterns specifically activated by H5N1, which, in contrast to low pathogenic influenza viruses, are responsible for an imbalance of an overwhelming proinflammatory and impaired antiviral gene program.
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Affiliation(s)
- Dorothee Viemann
- Institute of Immunology, University of Muenster, Muenster, Germany.
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19
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Glucocorticoids promote survival of anti-inflammatory macrophages via stimulation of adenosine receptor A3. Blood 2010; 116:446-55. [DOI: 10.1182/blood-2009-10-247106] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Abstract
Active resolution of inflammation is a previously unrecognized process essential for tissue homeostasis. Monocytes play a pivotal role in the generation as well as resolution of inflammation. Glucocorticoids (GCs) are widely used anti-inflammatory agents. We demonstrate that GCs exhibit antiapoptotic effects in monocytes resulting in differentiation to an anti-inflammatory phenotype. The molecular basis of this novel antiapoptotic effect is a prolonged activation of the extracellular signal regulated kinase/mitogen-activated protein kinase (ERK/MAPK) pathway resulting in inhibition of caspase activities and expression of antiapoptotic genes via activation of c-Myc. We identified up-regulation and activation of A3 adenosine receptor (A3AR) as the initial trigger of this antiapoptotic pathway. In summary, we deciphered a novel molecular pathway promoting survival of anti-inflammatory monocytes. Specific activation of A3AR or its downstream signaling pathways may thus be a novel strategy to modulate inflammation in autoimmune disorders with fewer side effects via induction of inflammatory resolution rather than immunosuppression.
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20
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Comparative pathogenesis and systems biology for biodefense virus vaccine development. J Biomed Biotechnol 2010; 2010:236528. [PMID: 20617142 PMCID: PMC2896660 DOI: 10.1155/2010/236528] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2009] [Revised: 01/21/2010] [Accepted: 03/08/2010] [Indexed: 11/18/2022] Open
Abstract
Developing vaccines to biothreat agents presents a number of challenges for discovery, preclinical development, and licensure. The need for high containment to work with live agents limits the amount and types of research that can be done using complete pathogens, and small markets reduce potential returns for industry. However, a number of tools, from comparative pathogenesis of viral strains at the molecular level to novel computational approaches, are being used to understand the basis of viral attenuation and characterize protective immune responses. As the amount of basic molecular knowledge grows, we will be able to take advantage of these tools not only to rationally attenuate virus strains for candidate vaccines, but also to assess immunogenicity and safety in silico. This review discusses how a basic understanding of pathogenesis, allied with systems biology and machine learning methods, can impact biodefense vaccinology.
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Landolin JM, Johnson DS, Trinklein ND, Aldred SF, Medina C, Shulha H, Weng Z, Myers RM. Sequence features that drive human promoter function and tissue specificity. Genome Res 2010; 20:890-8. [PMID: 20501695 DOI: 10.1101/gr.100370.109] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Promoters are important regulatory elements that contain the necessary sequence features for cells to initiate transcription. To functionally characterize a large set of human promoters, we measured the transcriptional activities of 4575 putative promoters across eight cell lines using transient transfection reporter assays. In parallel, we measured gene expression in the same cell lines and observed a significant correlation between promoter activity and endogenous gene expression (r = 0.43). As transient transfection assays directly measure the promoting effect of a defined fragment of DNA sequence, decoupled from epigenetic, chromatin, or long-range regulatory effects, we sought to predict whether a promoter was active using sequence features alone. CG dinucleotide content was highly predictive of ubiquitous promoter activity, necessitating the separation of promoters into two groups: high CG promoters, mostly ubiquitously active, and low CG promoters, mostly cell line-specific. Computational models trained on the binding potential of transcriptional factor (TF) binding motifs could predict promoter activities in both high and low CG groups: average area under the receiver operating characteristic curve (AUC) of the models was 91% and exceeded the AUC of CG content by an average of 23%. Known relationships, for example, between HNF4A and hepatocytes, were recapitulated in the corresponding cell lines, in this case the liver-derived cell line HepG2. Half of the associations between tissue-specific TFs and cell line-specific promoters were new. Our study underscores the importance of collecting functional information from complementary assays and conditions to understand biology in a systematic framework.
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Affiliation(s)
- Jane M Landolin
- Division of Life Sciences, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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TaNF-YC11, one of the light-upregulated NF-YC members in Triticum aestivum, is co-regulated with photosynthesis-related genes. Funct Integr Genomics 2010; 10:265-76. [PMID: 20111976 DOI: 10.1007/s10142-010-0158-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2009] [Revised: 12/27/2009] [Accepted: 01/01/2010] [Indexed: 10/19/2022]
Abstract
Nuclear factor Y (NF-Y) is a heterotrimeric transcription factor complex. Each of the NF-Y subunits (NF-YA, NF-YB and NF-YC) in plants is encoded by multiple genes. Quantitative RT-PCR analysis revealed that five wheat NF-YC members (TaNF-YC5, 8, 9, 11 and 12) were upregulated by light in both the leaf and seedling shoot. Co-expression analysis of Affymetrix wheat genome array datasets revealed that transcript levels of a large number of genes were consistently correlated with those of the TaNF-YC11 and TaNF-YC8 genes in three to four separate Affymetrix array datasets. TaNF-YC11-correlated transcripts were significantly enriched with the Gene Ontology term photosynthesis. Sequence analysis in the promoters of TaNF-YC11-correlated genes revealed the presence of putative NF-Y complex binding sites (CCAAT motifs). Quantitative RT-PCR analysis of a subset of potential TaNF-YC11 target genes showed that ten out of the 13 genes were also light-upregulated in both the leaf and seedling shoot and had significantly correlated expression profiles with TaNF-YC11. The potential target genes for TaNF-YC11 include subunit members from all four thylakoid membrane-bound complexes required for the conversion of solar energy into chemical energy and rate-limiting enzymes in the Calvin cycle. These data indicate that TaNF-YC11 is potentially involved in regulation of photosynthesis-related genes.
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23
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Yeh HY, Cheng SW, Lin YC, Yeh CY, Lin SF, Soo VW. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency. BMC Med Genomics 2009; 2:70. [PMID: 20025723 PMCID: PMC2805685 DOI: 10.1186/1755-8794-2-70] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2009] [Accepted: 12/21/2009] [Indexed: 02/07/2023] Open
Abstract
Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.
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Affiliation(s)
- Hsiang-Yuan Yeh
- Department of Computer Science, National Tsing Hua University, HsinChu 300, Taiwan.
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Cheng H, Jiang L, Wu M, Liu Q. Inferring Transcriptional Interactions by the Optimal Integration of ChIP-chip and Knock-out Data. Bioinform Biol Insights 2009; 3:129-40. [PMID: 20140075 PMCID: PMC2808186 DOI: 10.4137/bbi.s3445] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
How to combine heterogeneous data sources for reliable prediction of transcriptional regulation is a challenge. Here we present an easy but powerful method to integrate Chromatin immunoprecipitation (ChIP)-chip and knock-out data. Since these two types of data provide complementary (physical and functional) information about transcription, the method combining them is expected to achieve high detection rates and very low false positive rates. We try to seek the optimal integration of these two data using hyper-geometric distribution. We evaluate our method on yeast data and compare our predictions with YEASTRACT, high-quality ChIP-chip data, and literature. The results show that even using low-quality ChIP-chip data, our method uncovers more relations than those inferred before from high-quality data. Furthermore our method achieves a low false positive rate. We find experimental and computational evidence in literature for most transcription factor (TF)-gene relations uncovered by our method.
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Affiliation(s)
- Haoyu Cheng
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
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25
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Yeo ZX, Yeo HC, Yeo JKS, Yeo AL, Li Y, Clarke ND. Inferring transcription factor targets from gene expression changes and predicted promoter occupancy. J Comput Biol 2009; 16:357-68. [PMID: 19193152 DOI: 10.1089/cmb.2008.19tt] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
We have developed a method for inferring condition-specific targets of transcription factors based on ranking genes by gene expression change and ranking genes based on predicted transcription factor occupancy. The average of these two ranks, used as a test statistic, allows target genes to be inferred in a stringent manner. The method complements chromatin immunoprecipitation experiments by predicting targets under many conditions for which ChIP experiments have not been performed. We used the method to predict targets of 102 yeast transcription factors in approximately 1600 expression microarray experiments. The reliability of the method is suggested by the strong enrichment of genes previously shown to be bound, by the validation of binding to novel targets, by the way transcription factors with similar specificities can be functionally distinguished, and by the greater-than-expected number of regulatory network motifs, such as auto-regulatory interactions, that arise from new, predicted interactions. The combination of ChIP data and the targets inferred from this analysis results in a high-confidence regulatory network that includes many novel interactions. Interestingly, we find only a weak association between conditions in which we can infer the activity of a transcription factor and conditions in which the transcription gene itself is regulated. Thus, methods that rely on transcription factor regulation to help define regulatory interactions may miss regulatory relationships that are detected by the method reported here.
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26
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Liu LYD, Chen CY, Chen MJM, Tsai MS, Lee CHS, Phang TL, Chang LY, Kuo WH, Hwa HL, Lien HC, Jung SM, Lin YS, Chang KJ, Hsieh FJ. Statistical identification of gene association by CID in application of constructing ER regulatory network. BMC Bioinformatics 2009; 10:85. [PMID: 19292896 PMCID: PMC2679734 DOI: 10.1186/1471-2105-10-85] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2008] [Accepted: 03/17/2009] [Indexed: 02/01/2023] Open
Abstract
Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A). Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers. Availability the implementation of CID in R codes can be freely downloaded from .
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Affiliation(s)
- Li-Yu D Liu
- Department of Agronomy, Biometry Division, National Taiwan University, Taipei, Taiwan.
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Kristiansson E, Thorsen M, Tamás MJ, Nerman O. Evolutionary forces act on promoter length: identification of enriched cis-regulatory elements. Mol Biol Evol 2009; 26:1299-307. [PMID: 19258451 DOI: 10.1093/molbev/msp040] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Transcription factors govern gene expression by binding to short DNA sequences called cis-regulatory elements. These sequences are typically located in promoters, which are regions of variable length upstream of the open reading frames of genes. Here, we report that promoter length and gene function are related in yeast, fungi, and plants. In particular, the promoters for stress-responsive genes are in general longer than those of other genes. Essential genes have, on the other hand, relatively short promoters. We utilize these findings in a novel method for identifying relevant cis-regulatory elements in a set of coexpressed genes. The method is shown to generate more accurate results and fewer false positives compared with other common procedures. Our results suggest that genes with complex transcriptional regulation tend to have longer promoters than genes responding to few signals. This phenomenon is present in all investigated species, indicating that evolution adjust promoter length according to gene function. Identification of cis-regulatory elements in Saccharomyces cerevisiae can be done with the web service located at http://enricher.zool.gu.se.
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28
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Yang E, Yarmush ML, Androulakis IP. Transcription factor network reconstruction using the living cell array. J Theor Biol 2009; 256:393-407. [PMID: 18996398 PMCID: PMC3208267 DOI: 10.1016/j.jtbi.2008.09.040] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2008] [Revised: 08/28/2008] [Accepted: 09/26/2008] [Indexed: 12/16/2022]
Abstract
The objective of identifying transcriptional regulatory networks is to provide insights as to what governs an organism's long term response to external stimuli. We explore the coupling of the living cell array (LCA), a novel microfluidics device which utilizes fluorescence levels as a surrogate for transcription factor activity with reverse Euler deconvolution (RED) a computational technique proposed in this work to decipher the dynamics of the interactions. It is hypothesized that these two methods will allow us to first assess the underlying network architecture associated with the transcription factor network as well as specific mechanistic consequences of transcription factor activation such as receptor dimerization or tolerance. The overall approach identifies evidence of time-lagged response which may be indicative of mechanisms such as receptor dimerization, tolerance mechanisms which are evidence of various receptor mediated dynamics, and feedback loops which regulate the response of an organism to changing environmental conditions. Furthermore, through the exploration of multiple network architectures, we were able to obtain insights as to the role each transcription factor plays in the overall response and their overall redundancy in the organism's response to external perturbations. Thus, the LCA along with the proposed analysis technique is a valuable tool for identifying the possible architectures and mechanisms underlying the transcriptional response.
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Affiliation(s)
- Eric Yang
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA
| | - Martin L. Yarmush
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA
| | - Ioannis P. Androulakis
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA
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MicroRNAs as modulators of smoking-induced gene expression changes in human airway epithelium. Proc Natl Acad Sci U S A 2009; 106:2319-24. [PMID: 19168627 DOI: 10.1073/pnas.0806383106] [Citation(s) in RCA: 333] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
We have shown that smoking impacts bronchial airway gene expression and that heterogeneity in this response associates with smoking-related disease risk. In this study, we sought to determine whether microRNAs (miRNAs) play a role in regulating the airway gene expression response to smoking. We examined whole-genome miRNA and mRNA expression in bronchial airway epithelium from current and never smokers (n = 20) and found 28 miRNAs to be differentially expressed (P < 0.05) with the majority being down-regulated in smokers. We further identified a number of mRNAs whose expression level is highly inversely correlated with miRNA expression in vivo. Many of these mRNAs contain potential binding sites for the differentially expressed miRNAs in their 3'-untranslated region (UTR) and are themselves affected by smoking. We found that either increasing or decreasing the levels of mir-218 (a miRNA that is strongly affected by smoking) in both primary bronchial epithelial cells and H1299 cells was sufficient to cause a corresponding decrease or increase in the expression of predicted mir-218 mRNA targets, respectively. Further, mir-218 expression is reduced in primary bronchial epithelium exposed to cigarette smoke condensate (CSC), and alteration of mir-218 levels in these cells diminishes the induction of the predicted mir-218 target MAFG in response to CSC. These data indicate that mir-218 levels modulate the airway epithelial gene expression response to cigarette smoke and support a role for miRNAs in regulating host response to environmental toxins.
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Abstract
The availability of completely sequenced genomes and the wealth of literature on gene regulation have enabled researchers to model the transcriptional regulation system of some organisms in the form of a network. In order to reconstruct such networks in non-model organisms, three principal approaches have been taken. First, one can transfer the interactions between homologous components from a model organism to the organism of interest. Second, microarray experiments can be used to detect patterns in gene expression that stem from regulatory interactions. Finally, knowledge of experimentally characterized transcription factor binding sites can be used to analyze the promoter sequences in a genome in order to identify potential binding sites. In this chapter, we will focus in detail on the first approach and describe methods to reconstruct and analyze the transcriptional regulatory networks of uncharacterized organisms by using a known regulatory network as a template.
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Chorley BN, Wang X, Campbell MR, Pittman GS, Noureddine MA, Bell DA. Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: current and developing technologies. Mutat Res 2008; 659:147-57. [PMID: 18565787 PMCID: PMC2676583 DOI: 10.1016/j.mrrev.2008.05.001] [Citation(s) in RCA: 120] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2008] [Revised: 04/25/2008] [Accepted: 05/01/2008] [Indexed: 02/07/2023]
Abstract
The most common form of genetic variation, single nucleotide polymorphisms or SNPs, can affect the way an individual responds to the environment and modify disease risk. Although most of the millions of SNPs have little or no effect on gene regulation and protein activity, there are many circumstances where base changes can have deleterious effects. Non-synonymous SNPs that result in amino acid changes in proteins have been studied because of their obvious impact on protein activity. It is well known that SNPs within regulatory regions of the genome can result in disregulation of gene transcription. However, the impact of SNPs located in putative regulatory regions, or rSNPs, is harder to predict for two primary reasons. First, the mechanistic roles of non-coding genomic sequence remain poorly defined. Second, experimental validation of the functional consequences of rSNPs is often slow and laborious. In this review, we summarize traditional and novel methodologies for candidate rSNPs selection, in particular in silico techniques that aid in candidate rSNP selection. Additionally we will discuss molecular biological techniques that assess the impact of rSNPs on binding of regulatory machinery, as well as functional consequences on transcription. Standard techniques such as EMSA and luciferase reporter constructs are still widely used to assess effects of rSNPs on binding and gene transcription; however, these protocols are often bottlenecks in the discovery process. Therefore, we highlight novel and developing high-throughput protocols that promise to aid in shortening the process of rSNP validation. Given the large amount of genomic information generated from a multitude of re-sequencing and genome-wide SNP array efforts, future focus should be to develop validation techniques that will allow greater understanding of the impact these polymorphisms have on human health and disease.
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Affiliation(s)
- Brian N. Chorley
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Xuting Wang
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Michelle R. Campbell
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Gary S. Pittman
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Maher A. Noureddine
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Douglas A. Bell
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
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Yamamoto Y, Banas A, Murata S, Ishikawa M, Lim CR, Teratani T, Hatada I, Matsubara K, Kato T, Ochiya T. A comparative analysis of the transcriptome and signal pathways in hepatic differentiation of human adipose mesenchymal stem cells. FEBS J 2008; 275:1260-73. [PMID: 18318837 DOI: 10.1111/j.1742-4658.2008.06287.x] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The specific features of the plasticity of adult stem cells are largely unknown. Recently, we demonstrated the hepatic differentiation of human adipose tissue-derived mesenchymal stem cells (AT-MSCs). To identify the genes responsible for hepatic differentiation, we examined the gene expression profiles of AT-MSC-derived hepatocytes (AT-MSC-Hepa) using several microarray methods. The resulting sets of differentially expressed genes (1639 clones) were comprehensively analyzed to identify the pathways expressed in AT-MSC-Hepa. Clustering analysis revealed a striking similarity of gene clusters between AT-MSC-Hepa and the whole liver, indicating that AT-MSC-Hepa were similar to liver with regard to gene expression. Further analysis showed that enriched categories of genes and signaling pathways such as complementary activation and the blood clotting cascade in the AT-MSC-Hepa were relevant to liver-specific functions. Notably, decreases in Twist and Snail expression indicated that mesenchymal-to-epithelial transition occurred in the differentiation of AT-MSCs into hepatocytes. Our data show a similarity between AT-MSC-Hepa and the liver, suggesting that AT-MSCs are modulated by their environmental conditions, and that AT-MSC-Hepa may be useful in basic studies of liver function as well as in the development of stem cell-based therapy.
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Affiliation(s)
- Yusuke Yamamoto
- Section for Studies on Metastasis, National Cancer Center Research Institute, 1-1 Tsukiji 5-chome, Chuo-ku, Tokyo, Japan
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Ramsey SA, Klemm SL, Zak DE, Kennedy KA, Thorsson V, Li B, Gilchrist M, Gold ES, Johnson CD, Litvak V, Navarro G, Roach JC, Rosenberger CM, Rust AG, Yudkovsky N, Aderem A, Shmulevich I. Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics. PLoS Comput Biol 2008; 4:e1000021. [PMID: 18369420 PMCID: PMC2265556 DOI: 10.1371/journal.pcbi.1000021] [Citation(s) in RCA: 143] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2007] [Accepted: 02/04/2008] [Indexed: 01/04/2023] Open
Abstract
Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation. Macrophages play a vital role in host defense against infection by recognizing pathogens through pattern recognition receptors, such as the Toll-like receptors (TLRs), and mounting an immune response. Stimulation of TLRs initiates a complex transcriptional program in which induced transcription factor genes dynamically regulate downstream genes. Microarray-based transcriptional profiling has proved useful for mapping such transcriptional programs in simpler model organisms; however, mammalian systems present difficulties such as post-translational regulation of transcription factors, combinatorial gene regulation, and a paucity of available gene-knockout expression data. Additional evidence sources, such as DNA sequence-based identification of transcription factor binding sites, are needed. In this work, we computationally inferred a transcriptional network for TLR-stimulated murine macrophages. Our approach combined sequence scanning with time-course expression data in a probabilistic framework. Expression data were analyzed using the time-lagged correlation. A novel, unbiased method was developed to assess the significance of the time-lagged correlation. The inferred network of associations between transcription factor genes and co-expressed gene clusters was validated with targeted ChIP-on-chip experiments, and yielded insights into the macrophage activation program, including a potential novel regulator. Our general approach could be used to analyze other complex mammalian systems for which time-course expression data are available.
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Affiliation(s)
- Stephen A. Ramsey
- Institute for Systems Biology, Seattle, Washington, United States of America
- * E-mail: (SR); (AA); (IS)
| | - Sandy L. Klemm
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Daniel E. Zak
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Kathleen A. Kennedy
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Vesteinn Thorsson
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Bin Li
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Mark Gilchrist
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Elizabeth S. Gold
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Carrie D. Johnson
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Vladimir Litvak
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Garnet Navarro
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Jared C. Roach
- Institute for Systems Biology, Seattle, Washington, United States of America
| | | | - Alistair G. Rust
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Natalya Yudkovsky
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Alan Aderem
- Institute for Systems Biology, Seattle, Washington, United States of America
- * E-mail: (SR); (AA); (IS)
| | - Ilya Shmulevich
- Institute for Systems Biology, Seattle, Washington, United States of America
- * E-mail: (SR); (AA); (IS)
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Axelsen JB, Bernhardsson S, Sneppen K. One hub-one process: a tool based view on regulatory network topology. BMC SYSTEMS BIOLOGY 2008; 2:25. [PMID: 18318890 PMCID: PMC2292138 DOI: 10.1186/1752-0509-2-25] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2007] [Accepted: 03/04/2008] [Indexed: 11/25/2022]
Abstract
Background The relationship between the regulatory design and the functionality of molecular networks is a key issue in biology. Modules and motifs have been associated to various cellular processes, thereby providing anecdotal evidence for performance based localization on molecular networks. Results To quantify structure-function relationship we investigate similarities of proteins which are close in the regulatory network of the yeast Saccharomyces Cerevisiae. We find that the topology of the regulatory network only show weak remnants of its history of network reorganizations, but strong features of co-regulated proteins associated to similar tasks. These functional correlations decreases strongly when one consider proteins separated by more than two steps in the regulatory network. The network topology primarily reflects the processes that is orchestrated by each individual hub, whereas there is nearly no remnants of the history of protein duplications. Conclusion Our results suggests that local topological features of regulatory networks, including broad degree distributions, emerge as an implicit result of matching a number of needed processes to a finite toolbox of proteins.
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Affiliation(s)
- Jacob Bock Axelsen
- Centro de Astrobiología, Instituto Nacional de Técnica Aeroespacial, Ctra de Ajalvir km 4, 28850 Torrejón de Ardoz, Madrid, Spain.
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Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia. Genome Biol 2008; 9:R38. [PMID: 18291030 PMCID: PMC2374711 DOI: 10.1186/gb-2008-9-2-r38] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2007] [Revised: 01/01/2008] [Accepted: 02/21/2008] [Indexed: 01/04/2023] Open
Abstract
A dissection of the genetic networks and circuitries is described for two form of leukaemia. Integrating transcription factor binding and gene expression profiling, networks are revealed that underly this important human disease. Background Acute myeloid leukemia (AML) comprises a group of diseases characterized by the abnormal development of malignant myeloid cells. Recent studies have demonstrated an important role for aberrant transcriptional regulation in AML pathophysiology. Although several transcription factors (TFs) involved in myeloid development and leukemia have been studied extensively and independently, how these TFs coordinate with others and how their dysregulation perturbs the genetic circuitry underlying myeloid differentiation is not yet known. We propose an integrated approach for mammalian genetic network construction by combining the analysis of gene expression profiling data and the identification of TF binding sites. Results We utilized our approach to construct the genetic circuitries operating in normal myeloid differentiation versus acute promyelocytic leukemia (APL), a subtype of AML. In the normal and disease networks, we found that multiple transcriptional regulatory cascades converge on the TFs Rora and Rxra, respectively. Furthermore, the TFs dysregulated in APL participate in a common regulatory pathway and may perturb the normal network through Fos. Finally, a model of APL pathogenesis is proposed in which the chimeric TF PML-RARα activates the dysregulation in APL through six mediator TFs. Conclusion This report demonstrates the utility of our approach to construct mammalian genetic networks, and to obtain new insights regarding regulatory circuitries operating in complex diseases in humans.
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Jovel J, Walker M, Sanfaçon H. Recovery of Nicotiana benthamiana plants from a necrotic response induced by a nepovirus is associated with RNA silencing but not with reduced virus titer. J Virol 2007; 81:12285-97. [PMID: 17728227 PMCID: PMC2168989 DOI: 10.1128/jvi.01192-07] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2007] [Accepted: 08/20/2007] [Indexed: 02/06/2023] Open
Abstract
Recovery of plants from virus-induced symptoms is often described as a consequence of RNA silencing, an antiviral defense mechanism. For example, recovery of Nicotiana clevelandii from a nepovirus (tomato black ring virus) is associated with a decreased viral RNA concentration and sequence-specific resistance to further virus infection. In this study, we have characterized the interaction of another nepovirus, tomato ringspot virus (ToRSV), with host defense responses during symptom induction and subsequent recovery. Early in infection, ToRSV induced a necrotic phenotype in Nicotiana benthamiana that showed characteristics typical of a hypersensitive response. RNA silencing was also activated during ToRSV infection, as evidenced by the presence of ToRSV-derived small interfering RNAs (siRNAs) that could direct degradation of ToRSV sequences introduced into sensor constructs. Surprisingly, disappearance of symptoms was not accompanied by a commensurate reduction in viral RNA levels. The stability of ToRSV RNA after recovery was also observed in N. clevelandii and Cucumis sativus and in N. benthamiana plants carrying a functional RNA-dependent RNA polymerase 1 ortholog from Medicago truncatula. In experiments with a reporter transgene (green fluorescent protein), ToRSV did not suppress the initiation or maintenance of transgene silencing, although the movement of the silencing signal was partially hindered. Our results demonstrate that although RNA silencing is active during recovery, reduction of virus titer is not required for the initiation of this phenotype. This scenario adds an unforeseen layer of complexity to the interaction of nepoviruses with the host RNA silencing machinery. The possibility that viral proteins, viral RNAs, and/or virus-derived siRNAs inactivate host defense responses is discussed.
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Affiliation(s)
- Juan Jovel
- Pacific Agri-Food Research Centre, Agriculture and Agri-Food Canada, Summerland, BC, Canada
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Chawade A, Bräutigam M, Lindlöf A, Olsson O, Olsson B. Putative cold acclimation pathways in Arabidopsis thaliana identified by a combined analysis of mRNA co-expression patterns, promoter motifs and transcription factors. BMC Genomics 2007; 8:304. [PMID: 17764576 PMCID: PMC2001198 DOI: 10.1186/1471-2164-8-304] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2007] [Accepted: 09/02/2007] [Indexed: 01/08/2023] Open
Abstract
Background With the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes. However, relying solely on gene expression data may be of limited value if the aim is to infer the underlying genetic networks. Development of computational methods to combine microarray data with other information sources is therefore necessary. Here we describe one such method. Results By means of our method, previously published Arabidopsis microarray data from cold acclimated plants at six different time points, promoter motif sequence data extracted from ~24,000 Arabidopsis promoters and known transcription factor binding sites were combined to construct a putative genetic regulatory interaction network. The inferred network includes both previously characterised and hitherto un-described regulatory interactions between transcription factor (TF) genes and genes that encode other TFs or other proteins. Part of the obtained transcription factor regulatory network is presented here. More detailed information is available in the additional files. Conclusion The rule-based method described here can be used to infer genetic networks by combining data from microarrays, promoter sequences and known promoter binding sites. This method should in principle be applicable to any biological system. We tested the method on the cold acclimation process in Arabidopsis and could identify a more complex putative genetic regulatory network than previously described. However, it should be noted that information on specific binding sites for individual TFs were in most cases not available. Thus, gene targets for the entire TF gene families were predicted. In addition, the networks were built solely by a bioinformatics approach and experimental verifications will be necessary for their final validation. On the other hand, since our method highlights putative novel interactions, more directed experiments could now be performed.
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Affiliation(s)
- Aakash Chawade
- Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden
- School of Humanities and Informatics, University of Skövde, Box 408, 541 28 Skövde, Sweden
| | - Marcus Bräutigam
- Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden
| | - Angelica Lindlöf
- School of Humanities and Informatics, University of Skövde, Box 408, 541 28 Skövde, Sweden
| | - Olof Olsson
- Department of Cell and Molecular Biology, Göteborg University, Box 462, 403 20 Göteborg, Sweden
| | - Björn Olsson
- School of Humanities and Informatics, University of Skövde, Box 408, 541 28 Skövde, Sweden
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Tabach Y, Brosh R, Buganim Y, Reiner A, Zuk O, Yitzhaky A, Koudritsky M, Rotter V, Domany E. Wide-scale analysis of human functional transcription factor binding reveals a strong bias towards the transcription start site. PLoS One 2007; 2:e807. [PMID: 17726537 PMCID: PMC1950076 DOI: 10.1371/journal.pone.0000807] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2007] [Accepted: 07/24/2007] [Indexed: 01/07/2023] Open
Abstract
Background Transcription factors (TF) regulate expression by binding to specific DNA sequences. A binding event is functional when it affects gene expression. Functionality of a binding site is reflected in conservation of the binding sequence during evolution and in over represented binding in gene groups with coherent biological functions. Functionality is governed by several parameters such as the TF-DNA binding strength, distance of the binding site from the transcription start site (TSS), DNA packing, and more. Understanding how these parameters control functionality of different TFs in different biological contexts is a must for identifying functional TF binding sites and for understanding regulation of transcription. Methodology/Principal Findings We introduce a novel method to screen the promoters of a set of genes with shared biological function (obtained from the functional Gene Ontology (GO) classification) against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. More than 8000 human (and 23,000 mouse) genes, were assigned to one of 134 GO sets. Their promoters were searched (from 200 bp downstream to 1000 bp upstream the TSS) for 414 known DNA motifs. We optimized the sequence similarity score threshold, independently for every location window, taking into account nucleotide heterogeneity along the promoters of the target genes. The method, combined with binding sequence and location conservation between human and mouse, identifies with high probability functional binding sites for groups of functionally-related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were tested experimentally. Conclusions/Significance We identified reliably functional TF binding sites. This is an essential step towards constructing regulatory networks. The promoter region proximal to the TSS is of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.
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Affiliation(s)
- Yuval Tabach
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel
| | - Ran Brosh
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel
| | - Yossi Buganim
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel
| | - Anat Reiner
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
| | - Or Zuk
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
| | - Assif Yitzhaky
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
| | - Mark Koudritsky
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
| | - Varda Rotter
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel
| | - Eytan Domany
- Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel
- * To whom correspondence should be addressed. E-mail:
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Xi H, Yu Y, Fu Y, Foley J, Halees A, Weng Z. Analysis of overrepresented motifs in human core promoters reveals dual regulatory roles of YY1. Genome Res 2007; 17:798-806. [PMID: 17567998 PMCID: PMC1891339 DOI: 10.1101/gr.5754707] [Citation(s) in RCA: 91] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
A set of 723 high-quality human core promoter sequences were compiled and analyzed for overrepresented motifs. Beside the two well-characterized core promoter motifs (TATA and Inr), several known motifs (YY1, Sp1, NRF-1, NRF-2, CAAT, and CREB) and one potentially new motif (motif8) were found. Interestingly, YY1 and motif8 mostly reside immediately downstream from the TSS. In particular, the YY1 motif occurs primarily in genes with 5'-UTRs shorter than 40 base pairs (bp) and its locations coincide with the translation start site. We verified that the YY1 motif is bound by YY1 in vitro. We then performed detailed analysis on YY1 chromatin immunoprecipitation data with a whole-genome human promoter microarray (ChIP-chip) and revealed that the thus identified promoters in HeLa cells were highly enriched with the YY1 motif. Moreover, the motif overlapped with the translation start sites on the plus strand of a group of genes, many with short 5'-UTRs, and with the transcription start sites on the minus strand of another distinct group of genes; together, the two groups of genes accounted for the majority of the YY1-bound promoters in the ChIP-chip data. Furthermore, the first group of genes was highly enriched in the functional categories of ribosomal proteins and nuclear-encoded mitochondria proteins. We suggest that the YY1 motif plays a dual role in both transcription and translation initiation of these genes. We also discuss the evolutionary advantages of housing a transcriptional element inside the transcript in terms of the migration of these genes in the human genome.
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Affiliation(s)
- Hualin Xi
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Yong Yu
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Yutao Fu
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Jonathan Foley
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
| | - Anason Halees
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
| | - Zhiping Weng
- Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
- Corresponding author.E-mail ; fax (617) 353-6766
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Jin VX, O’Geen H, Iyengar S, Green R, Farnham PJ. Identification of an OCT4 and SRY regulatory module using integrated computational and experimental genomics approaches. Genome Res 2007; 17:807-17. [PMID: 17567999 PMCID: PMC1891340 DOI: 10.1101/gr.6006107] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
ChIP-chip studies have revealed that many in vivo binding sites have a weak match to the consensus sequence for the transcription factor being analyzed. Possible explanations for these observations include (1) the in vitro-derived consensus site does not represent the in vivo binding site and/or (2) the factor is recruited to a weak binding site via interaction with another protein. To address these possibilities, we developed an approach (ChIPMotifs) that incorporates a bootstrap resampling method to statistically infer the optimal cutoff threshold for a position weight matrix (PWM) of a motif identified from ChIP-chip data by ab initio motif discovery programs. Using OCT4 ChIP-chip data and the ChIPMotifs approach, we first developed a refined OCT4 PWM. We then used the refined PWM and a ChIPModules approach to identify transcription factors colocalizing with OCT4 in Ntera2 testicular embryonal carcinoma cells. We found that the consensus binding site for SRY, a transcription factor critical for testis development, colocalizes with the OCT4 PWM. To further characterize the relationship between OCT4 and SRY, we performed ChIP-chip experiments with human promoter microarrays, and found that 49% of the top approximately 1000 OCT4 target promoters were also bound by SRY. This analysis represents the first identification of SRY target promoters. Interestingly, we determined that promoters bound by OCT4 and SRY, but not those bound by SRY alone, were also bound by the transcriptional repressor KAP1. Our studies not only validate the ChIPMotifs and ChIPModules combinatorial approach but also identify a possible new regulatory partner of OCT4.
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Affiliation(s)
- Victor X. Jin
- Department of Pharmacology and the Genome Center, University of California–Davis, Davis, California 95616, USA
| | - Henriette O’Geen
- Department of Pharmacology and the Genome Center, University of California–Davis, Davis, California 95616, USA
| | - Sushma Iyengar
- Department of Pharmacology and the Genome Center, University of California–Davis, Davis, California 95616, USA
| | - Roland Green
- NimbleGen Systems, Inc., Madison, Wisconsin 53711, USA
| | - Peggy J. Farnham
- Department of Pharmacology and the Genome Center, University of California–Davis, Davis, California 95616, USA
- Corresponding author.E-mail ; fax (530) 754-9658
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Lin JM, Collins PJ, Trinklein ND, Fu Y, Xi H, Myers RM, Weng Z. Transcription factor binding and modified histones in human bidirectional promoters. Genome Res 2007; 17:818-27. [PMID: 17568000 PMCID: PMC1891341 DOI: 10.1101/gr.5623407] [Citation(s) in RCA: 104] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Bidirectional promoters have received considerable attention because of their ability to regulate two downstream genes (divergent genes). They are also highly abundant, directing the transcription of approximately 11% of genes in the human genome. We categorized the presence of DNA sequence motifs, binding of transcription factors, and modified histones as overrepresented, shared, or underrepresented in bidirectional promoters with respect to unidirectional promoters. We found that a small set of motifs, including GABPA, MYC, E2F1, E2F4, NRF-1, CCAAT, YY1, and ACTACAnnTCC are overrepresented in bidirectional promoters, while the majority (73%) of known vertebrate motifs are underrepresented. We performed chromatin-immunoprecipitation (ChIP), followed by quantitative PCR for GABPA, on 118 regions in the human genome and showed that it binds to bidirectional promoters more frequently than unidirectional promoters, and its position-specific scoring matrix is highly predictive of binding. Signatures of active transcription, such as occupancy of RNA polymerase II and the modified histones H3K4me2, H3K4me3, and H3ac, are overrepresented in regions around bidirectional promoters, suggesting that a higher fraction of divergent genes are transcribed in a given cell than the fraction of other genes. Accordingly, analysis of whole-genome microarray data indicates that 68% of divergent genes are transcribed compared with 44% of all human genes. By combining the analysis of publicly available ENCODE data and a detailed study of GABPA, we survey bidirectional promoters with breadth and depth, leading to biological insights concerning their motif composition and bidirectional regulatory mode.
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Affiliation(s)
- Jane M. Lin
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215, USA
| | - Patrick J. Collins
- Department of Genetics, Stanford University, School of Medicine, Stanford, California 94305-5120, USA
| | - Nathan D. Trinklein
- Department of Genetics, Stanford University, School of Medicine, Stanford, California 94305-5120, USA
| | - Yutao Fu
- Program in Bioinformatics and Systems Biology, Boston University, Boston, Massachusetts, 02215, USA
| | - Hualin Xi
- Program in Bioinformatics and Systems Biology, Boston University, Boston, Massachusetts, 02215, USA
| | - Richard M. Myers
- Department of Genetics, Stanford University, School of Medicine, Stanford, California 94305-5120, USA
| | - Zhiping Weng
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215, USA
- Program in Bioinformatics and Systems Biology, Boston University, Boston, Massachusetts, 02215, USA
- Corresponding author.E-mail ; fax (617) 353-6766
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Optimization of reporter gene assay: several factors influencing detection of promoter activity. Chin Med J (Engl) 2007. [DOI: 10.1097/00029330-200706010-00005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Chang LW, Fontaine BR, Stormo GD, Nagarajan R. PAP: a comprehensive workbench for mammalian transcriptional regulatory sequence analysis. Nucleic Acids Res 2007; 35:W238-44. [PMID: 17517777 PMCID: PMC1933204 DOI: 10.1093/nar/gkm308] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Given the recent explosion of publications that employ microarray technology to monitor genome-wide expression and that correlate these expression changes to biological processes or to disease states, the determination of the transcriptional regulation of these co-expressed genes is the next major step toward deciphering the genetic network governing the pathway or disease under study. Although computational approaches have been proposed for this purpose, there is no integrated and user-friendly software application that allows experimental biologists to tackle this problem in higher eukaryotes. We have previously reported a systematic, statistical model of mammalian transcriptional regulatory sequence analysis. We have now made crucial extensions to this model and have developed a comprehensive, user-friendly web application suite termed the Promoter Analysis Pipeline (PAP). PAP is available at: http://bioinformatics.wustl.edu/webTools/portalModule/PromoterSearch.do
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Affiliation(s)
- Li-Wei Chang
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA and Department of Pathology and Immunology, Division of Laboratory Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Burr R. Fontaine
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA and Department of Pathology and Immunology, Division of Laboratory Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Gary D. Stormo
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA and Department of Pathology and Immunology, Division of Laboratory Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Rakesh Nagarajan
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA and Department of Pathology and Immunology, Division of Laboratory Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
- *To whom correspondence should be addressed. (314)362-8859 (314)454-5208
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Julià A, Moore J, Miquel L, Alegre C, Barceló P, Ritchie M, Marsal S. Identification of a two-loci epistatic interaction associated with susceptibility to rheumatoid arthritis through reverse engineering and multifactor dimensionality reduction. Genomics 2007; 90:6-13. [PMID: 17482423 DOI: 10.1016/j.ygeno.2007.03.011] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2006] [Revised: 02/15/2007] [Accepted: 03/08/2007] [Indexed: 11/29/2022]
Abstract
Altered synovial fibroblast (SF) transcriptional activity is a key factor in the disease progression of rheumatoid arthritis (RA). To determine the transcriptional regulatory network associated with SF response to an RA proinflammatory stimulus we applied a CARRIE reverse engineering approach to microarray gene expression data from SFs treated with RA synovial fluid. The association of the inferred gene network with RA susceptibility was further analyzed by a case-control study of promoter single-nucleotide polymorphisms, and the presence of epistatic interactions was determined using the multifactor dimensionality reduction methodology. Our findings suggest that a specific NF-kappaB transcriptional regulatory network of 13 genes is associated with SF response to RA proinflammatory stimulus and identify a significant epistatic association of two of its genes, IL6 and IL4I1, with RA susceptibility.
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Affiliation(s)
- Antonio Julià
- Unitat de Recerca de Reumatologia, Institut de Recerca Hospital Universitari Vall d'Hebron, UAB, 08035 Barcelona, Spain
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Wang X, Tomso DJ, Chorley BN, Cho HY, Cheung VG, Kleeberger SR, Bell DA. Identification of polymorphic antioxidant response elements in the human genome. Hum Mol Genet 2007; 16:1188-200. [PMID: 17409198 PMCID: PMC2805149 DOI: 10.1093/hmg/ddm066] [Citation(s) in RCA: 125] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBSs) may affect the binding of transcription factors, lead to differences in gene expression and phenotypes and therefore affect susceptibility to environmental exposure. We developed an integrated computational system for discovering functional SNPs in TFBSs in the human genome and predicting their impact on the expression of target genes. In this system, we (i) construct a position weight matrix (PWM) from a collection of experimentally discovered TFBSs; (ii) predict TFBSs in SNP sequences using the PWM and map SNPs to the upstream regions of genes; (iii) examine the evolutionary conservation of putative TFBSs by phylogenetic footprinting; (iv) prioritize candidate SNPs based on microarray expression profiles from tissues in which the transcription factor of interest is either deleted or over-expressed and (v) finally, analyze association of SNP genotypes with gene expression phenotypes. The application of our system has been tested to identify functional polymorphisms in the antioxidant response element (ARE), a cis-acting enhancer sequence found in the promoter region of many genes that encode antioxidant and Phase II detoxification enzymes/proteins. In response to oxidative stress, the transcription factor NRF2 (nuclear factor erythroid-derived 2-like 2) binds to AREs, mediating transcriptional activation of its responsive genes and modulating in vivo defense mechanisms against oxidative damage. Using our novel computational tools, we have identified a set of polymorphic AREs with functional evidence, showing the utility of our system to direct further experimental validation of genomic sequence variations that could be useful for identifying high-risk individuals.
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Affiliation(s)
- Xuting Wang
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Daniel J. Tomso
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Brian N. Chorley
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Hye-Youn Cho
- Laboratory of Respiratory Biology, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Vivian G. Cheung
- Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104
| | - Steven R. Kleeberger
- Laboratory of Respiratory Biology, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
| | - Douglas A. Bell
- Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709
- To whom all correspondence should be addressed: Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, Mail Drop: C3-03, 111 TW Alexander Drive, PO Box 12233, Research Triangle Park, NC 27709., Tel: 919-541-7686, Fax: 919-541-7593,
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46
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Wang LY, Snyder M, Gerstein M. BoCaTFBS: a boosted cascade learner to refine the binding sites suggested by ChIP-chip experiments. Genome Biol 2007; 7:R102. [PMID: 17078876 PMCID: PMC1794589 DOI: 10.1186/gb-2006-7-11-r102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2006] [Revised: 08/29/2006] [Accepted: 11/01/2006] [Indexed: 11/23/2022] Open
Abstract
BoCaTFBS, a new method that combines noisy data from ChIP-chip experiments with known binding-site patterns, is described and applied to the ENCODE project. Comprehensive mapping of transcription factor binding sites is essential in postgenomic biology. For this, we propose a mining approach combining noisy data from ChIP (chromatin immunoprecipitation)-chip experiments with known binding site patterns. Our method (BoCaTFBS) uses boosted cascades of classifiers for optimum efficiency, in which components are alternating decision trees; it exploits interpositional correlations; and it explicitly integrates massive negative information from ChIP-chip experiments. We applied BoCaTFBS within the ENCODE project and showed that it outperforms many traditional binding site identification methods (for instance, profiles).
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Affiliation(s)
- Lu-yong Wang
- Integrated Data Systems Department, Siemens Corporate Research, 755 College Road East, Princeton, New Jersey 08540, USA
| | - Michael Snyder
- Department of Molecular, Cellular, and Developmental Biology, KBT 926, 266 Whitney Ave, Yale University, New Haven, Connecticut 06520, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Bass 432A, 266 Whitney Ave, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Bass 432A, 266 Whitney Ave, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, 51 Prospect Street, Yale University, New Haven, Connecticut 06520, USA
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Itaya A, Zhong X, Bundschuh R, Qi Y, Wang Y, Takeda R, Harris AR, Molina C, Nelson RS, Ding B. A structured viroid RNA serves as a substrate for dicer-like cleavage to produce biologically active small RNAs but is resistant to RNA-induced silencing complex-mediated degradation. J Virol 2007; 81:2980-94. [PMID: 17202210 PMCID: PMC1865973 DOI: 10.1128/jvi.02339-06] [Citation(s) in RCA: 163] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2006] [Accepted: 12/21/2006] [Indexed: 11/20/2022] Open
Abstract
RNA silencing is a potent means of antiviral defense in plants and animals. A hallmark of this defense response is the production of 21- to 24-nucleotide viral small RNAs via mechanisms that remain to be fully understood. Many viruses encode suppressors of RNA silencing, and some viral RNAs function directly as silencing suppressors as counterdefense. The occurrence of viroid-specific small RNAs in infected plants suggests that viroids can trigger RNA silencing in a host, raising the question of how these noncoding and unencapsidated RNAs survive cellular RNA-silencing systems. We address this question by characterizing the production of small RNAs of Potato spindle tuber viroid (srPSTVds) and investigating how PSTVd responds to RNA silencing. Our molecular and biochemical studies provide evidence that srPSTVds were derived mostly from the secondary structure of viroid RNAs. Replication of PSTVd was resistant to RNA silencing, although the srPSTVds were biologically active in guiding RNA-induced silencing complex (RISC)-mediated cleavage, as shown with a sensor system. Further analyses showed that without possessing or triggering silencing suppressor activities, the PSTVd secondary structure played a critical role in resistance to RISC-mediated cleavage. These findings support the hypothesis that some infectious RNAs may have evolved specific secondary structures as an effective means to evade RNA silencing in addition to encoding silencing suppressor activities. Our results should have important implications in further studies on RNA-based mechanisms of host-pathogen interactions and the biological constraints that shape the evolution of infectious RNA structures.
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Affiliation(s)
- Asuka Itaya
- Department of Plant Cellular and Molecular Biology and Plant Biotechnology Center, Ohio State University, 207 Rightmire Hall, 1060 Carmack Road, Columbus, OH 43210, USA
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48
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Holloway DT, Kon M, DeLisi C. Machine learning for regulatory analysis and transcription factor target prediction in yeast. SYSTEMS AND SYNTHETIC BIOLOGY 2007; 1:25-46. [PMID: 19003435 PMCID: PMC2533145 DOI: 10.1007/s11693-006-9003-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
High throughput technologies, including array-based chromatin immunoprecipitation, have rapidly increased our knowledge of transcriptional maps-the identity and location of regulatory binding sites within genomes. Still, the full identification of sites, even in lower eukaryotes, remains largely incomplete. In this paper we develop a supervised learning approach to site identification using support vector machines (SVMs) to combine 26 different data types. A comparison with the standard approach to site identification using position specific scoring matrices (PSSMs) for a set of 104 Saccharomyces cerevisiae regulators indicates that our SVM-based target classification is more sensitive (73 vs. 20%) when specificity and positive predictive value are the same. We have applied our SVM classifier for each transcriptional regulator to all promoters in the yeast genome to obtain thousands of new targets, which are currently being analyzed and refined to limit the risk of classifier over-fitting. For the purpose of illustration we discuss several results, including biochemical pathway predictions for Gcn4 and Rap1. For both transcription factors SVM predictions match well with the known biology of control mechanisms, and possible new roles for these factors are suggested, such as a function for Rap1 in regulating fermentative growth. We also examine the promoter melting temperature curves for the targets of YJR060W, and show that targets of this TF have potentially unique physical properties which distinguish them from other genes. The SVM output automatically provides the means to rank dataset features to identify important biological elements. We use this property to rank classifying k-mers, thereby reconstructing known binding sites for several TFs, and to rank expression experiments, determining the conditions under which Fhl1, the factor responsible for expression of ribosomal protein genes, is active. We can see that targets of Fhl1 are differentially expressed in the chosen conditions as compared to the expression of average and negative set genes. SVM-based classifiers provide a robust framework for analysis of regulatory networks. Processing of classifier outputs can provide high quality predictions and biological insight into functions of particular transcription factors. Future work on this method will focus on increasing the accuracy and quality of predictions using feature reduction and clustering strategies. Since predictions have been made on only 104 TFs in yeast, new classifiers will be built for the remaining 100 factors which have available binding data.
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Affiliation(s)
- Dustin T. Holloway
- Molecular Biology Cell Biology and Biochemistry, Boston University, Boston, MA 02215 USA
| | - Mark Kon
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215 USA
- Bioinformatics and Systems Biology, Boston University, Boston, MA 02215 USA
| | - Charles DeLisi
- Bioinformatics and Systems Biology, Boston University, Boston, MA 02215 USA
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49
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Hartman ZC, Black EP, Amalfitano A. Adenoviral infection induces a multi-faceted innate cellular immune response that is mediated by the toll-like receptor pathway in A549 cells. Virology 2007; 358:357-72. [PMID: 17027060 DOI: 10.1016/j.virol.2006.08.041] [Citation(s) in RCA: 68] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2006] [Revised: 07/18/2006] [Accepted: 08/23/2006] [Indexed: 01/15/2023]
Abstract
Adenovirus vectors are known to induce certain genes and impact innate response networks, but a broad understanding of this process and its mechanisms is currently lacking. For this reason, we chose to investigate and characterize Ad innate immunity using homogeneous, primary MEF cells replete with all the elements of the pathogen-sensing Toll-Like Receptor (TLR) pathway. By using an array-based approach to maximally define transcriptome changes induced upon Ad vector infection, we discovered that Ad infection induces a potent gene and transcription factor network response. This response is characterized by significant changes in the expression of genes involved in focal adhesion, tight junction, and RNA regulation, in addition to TLR pathway and other innate sensing genes. Further investigation using human A549 cells knocked down for various TLR pathway adaptors, revealed significant impacts on the Ad initiation of NF-kB and interferon responses, thus confirming TLR involvement in Ad-mediated immunity across diverse species.
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Affiliation(s)
- Zachary C Hartman
- Division of Medical Genetics, Department of Pediatrics, Duke University Medical Center, Durham, North Carolina 27710, USA
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50
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Buck MJ, Lieb JD. A chromatin-mediated mechanism for specification of conditional transcription factor targets. Nat Genet 2006; 38:1446-51. [PMID: 17099712 PMCID: PMC2756100 DOI: 10.1038/ng1917] [Citation(s) in RCA: 78] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2006] [Accepted: 10/04/2006] [Indexed: 01/17/2023]
Abstract
Organisms respond to changes in their environment, and many such responses are initiated at the level of gene transcription. Here, we provide evidence for a previously undiscovered mechanism for directing transcriptional regulators to new binding targets in response to an environmental change. We show that repressor-activator protein 1 (Rap1), a master regulator of yeast metabolism, binds to an expanded target set after glucose depletion despite decreasing protein levels and no evidence of posttranslational modification. Computational analysis predicts that proteins capable of recruiting the chromatin regulator Tup1 act to restrict the binding distribution of Rap1 in the presence of glucose. Deletion of the gene(s) encoding Tup1, recruiters of Tup1 or chromatin regulators recruited by Tup1 cause Rap1 to bind specifically and inappropriately to low-glucose targets. These data, combined with whole-genome measurements of nucleosome occupancy and Tup1 distribution, provide evidence for a mechanism of dynamic target specification that coordinates the genome-wide distribution of intermediate-affinity DNA sequence motifs with chromatin-mediated regulation of accessibility to those sites.
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Affiliation(s)
- Michael J Buck
- Department of Biology and the Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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