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Enterococcus faecalis reconfigure the activation of its transcriptional regulatory networks under different copper exposure levels

ABSTRACT: The microarrays experiments was performed with the purpose of identify transcriptional networks activated by copper. This experiment correspond the work tituled Enterococcus faecalis reconfigure the activation of its transcriptional regulatory networks under different copper exposure levels (work in preparation).Mauricio Latorrea,b, Jessica Galloway-Peñac,d,e, Jung Hyeo Rhoc,d, Marko Budinichf, Barbara E. Murrayc,d,e, Alejandro Maassb,f, Mauricio Gonzáleza,b,f*. a INTA, Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile. b Center for Genome Regulation (Fondap 15090007), University of Chile, Santiago, Chile. c Division of Infectious Disease, Department of Medicine, University of Texas Medical School, Houston, Texas, United States of America. d Center for the Study of Emerging and Reemerging Pathogens, University of Texas Medical School, Houston, Texas, United States of America. e Department of Microbiology and Molecular Genetics, University of Texas Medical School, Houston, Texas, United States of America f Mathomics, Center for Mathematical Modeling (UMI2807CNRS), Santiago, Chile. * Corresponding author. Address: El Líbano 5524, Santiago 11, Chile. Fax: +56 (2) 2214030.

ORGANISM(S): Enterococcus faecalis V583 Enterococcus faecalis OG1RF

PROVIDER: GSE45131 | GEO | 2013/11/12

SECONDARY ACCESSION(S): PRJNA192944

REPOSITORIES: GEO

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Enterococcus faecalis reconfigure the activation of its transcriptional regulatory networks under different copper exposure levels

Project description:The microarrays experiments was performed with the purpose of identify transcriptional networks activated by copper. This experiment correspond the work tituled Enterococcus faecalis reconfigure the activation of its transcriptional regulatory networks under different copper exposure levels (work in preparation).Mauricio Latorrea,b, Jessica Galloway-PeM-CM-1ac,d,e, Jung Hyeo Rhoc,d, Marko Budinichf, Barbara E. Murrayc,d,e, Alejandro Maassb,f, Mauricio GonzM-CM-!leza,b,f*. a INTA, Laboratorio de BioinformM-CM-!tica y ExpresiM-CM-3n GM-CM-)nica, INTA, Universidad de Chile, Santiago, Chile. b Center for Genome Regulation (Fondap 15090007), University of Chile, Santiago, Chile. c Division of Infectious Disease, Department of Medicine, University of Texas Medical School, Houston, Texas, United States of America. d Center for the Study of Emerging and Reemerging Pathogens, University of Texas Medical School, Houston, Texas, United States of America. e Department of Microbiology and Molecular Genetics, University of Texas Medical School, Houston, Texas, United States of America f Mathomics, Center for Mathematical Modeling (UMI2807CNRS), Santiago, Chile. * Corresponding author. Address: El LM-CM--bano 5524, Santiago 11, Chile. Fax: +56 (2) 2214030. A eight chip study (two technical replicates) using total RNA recovered from four separate cultures of: Enterococcus faecalis OG1RF (N medium growth), Enterococcus faecalis OG1RF copM-NM-^T mutant strain (N medium growth), Enterococcus faecalis OG1RF copM-NM-^T mutant low copper treatment (N medium growth + 0.05 mM CuSO4) and Enterococcus faecalis OG1RF copM-NM-^T mutant low copper treatment (N medium growth + 0.5 mM CuSO4). Each chip measures the expression level of 3,114 genome genes from Enterococcus faecalis strain V583 (A7980-00-01).

2013-11-12 | E-GEOD-45131 | biostudies-arrayexpress

Viladomiu2012 - PPARgamma role in C.diff associated disease

Project description:"Modeling the Role of Peroxisome Proliferator-Activated Receptor γ and MicroRNA-146 in Mucosal Immune Responses to Clostridium difficile" Monica Viladomiu1,2, Raquel Hontecillas1,2, Mireia Pedragosa1,2, Adria Carbo1,2, Stefan Hoops1,2, Pawel Michalak4,5, Katarzyna Michalak4, Richard L. Guerrant2,3, James K. Roche2,3, Cirle A. Warren2,3, Josep Bassaganya-Riera1,2* 1) Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America, 2) Center for Modeling Immunity to Enteric Pathogens, Virginia Tech, Blacksburg, Virginia, United States of America, 3) Division of Infectious Disease and International Health, Center for Global Health, University of Virginia, Charlottesville, Virginia, United States of America, 4) Medical Informatics and Systems Division, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America, 5) Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America E-mail: jbassaga@vt.edu This model represents the interaction between Cdiff, miRNA146b, NCOA4, PPARg, IL10 and IL17. Simulation studies show an aberrant expression of miRNA146b with increasing concentrations of Cdiff over time, which results in decreased PPARg activation due to NCOA4 inhibition. As a final result, PPARg is unable to modulate effector and regulatory responses, since results show an upregulation of IL17 expression and downregulation of IL10 production.

2005-01-01 | MODEL1210260004 | BioModels

Prinary breast cancers and brain metastasis

Project description:Sixteen paired matched samples from primary breast cancers and brain metastases diagnosed between April 1, 2001 and December 31, 2012 were collected from 8 institutions. Brain metastases were identified based on magnetic resonance imaging and/or computed tomography findings. The clinical characteristics of all the patients were obtained from their medical records. This study was approved by the institutional review board of each participating institute (Tokai University School of Medicine; National Hospital Organization Osaka National Hospital; Kinki University School of Medicine; Niigata Cancer Center Hospital; Shizuoka General Hospital; Hokkaido Cancer Center; National Hospital Organization, Tokyo Medical Center; and Gunma Prefectural Cancer Center). Matching primary breast cancers and brain metastases Formalin-Fixed Paraffin-Embedded (FFPE) specimens for gene expression analysis were collected into RNA. RNA from specimens was isolated, and quantity and quality of the each RNA was using an Agilent 2100 Bioanalyzer (Agilent Technologies). Genome-wide expression levels of transcripts were analyzed using the Affymetrix U133A gene chips (Affymetrix) according to the manufacture’s instructions.

2019-09-25 | GSE125989 | GEO

Major MLL fusion partners regulate promoter-proximal pausing and release of RNA polymerase II

Project description:1Sheng Yushou Center of Cell Biology and Immunology, Department of Genetics and Developmental Biology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. 2Laboratory of Biochemistry and Molecular Biology, The Rockefeller University, New York, NY 10065, USA. 3Systems Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA. 4CCTS Bioinformatic Program, The Rockefeller University, New York, NY 10065, USA. 5State Key Laboratory of Genetic Engineering & Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China

2021-06-30 | GSE84157 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of transcriptomes in MM.1S cells treated with DMSO, All-trans retinoic acid (ATRA), carfilzomib (Cfz), and their combinations

Project description:ATRA is important for sensitizing MM cells to Cfz. To determine what signalling pathways are affected by ATRA+Cfz in MM cells, MM.1S MM cell line was pulsed with Cfz and then cultured with DMSO or 10µM ATRA for 12 h. Total RNAs of 2 x 106 MM.1S cells for each sample were extracted by RNeasy Mini Kit (Qiagen). 5-10 µg RNA samples were sent to Cancer Genomics Center at The University of Texas (Houston, TX) for genearray followed by data analysis. We use gene experssion profiling data to determine differential expression of genes in MM cells in culture with DMSO, ATRA, Cfz or ATRA+Cfz.

2021-12-31 | GSE178340 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of transcriptomes in CTR-KD ARP-1 cells and LILRB1-KD ARP-1 cells sorted from the bone marrow of NSG mice transplanted with these cells

Project description:To determine what signalling pathways are affected by LILRB1 in MM cells, ARP-1 MM cell lines were transfected with lentivirus to knockdown LILRB1, injected to nsg mice, sorted from the bone marrow of NSG mice and sent for RNA-seq. Total RNAs of 2 x 10^6 CTR-KD ARP-1 cells or LILRB1-KD ARP-1 cells were extracted by RNeasy Mini Kit (Qiagen). 5-10 µg RNA samples were sent to Cancer Genomics Center at The University of Texas (Houston, TX) for RNA-seq followed by data analysis. We use the RNA-seq data to determine differential expression of genes in CTR-KD ARP-1 cells and LILRB1-KD ARP-1 cells.

2024-03-07 | GSE226821 | GEO

Rhesus Macaque Model of Mismatch Repair-Deficient Colorectal Cancer

Project description:This SuperSeries is composed of the SubSeries listed below. NIH grant(s): Grant ID: 5 P30 CA016672-44 Grant title: Cancer Center Support Grant Affiliation: The University of Texas MD Anderson Cancer Center Grantor: NCI

2022-03-31 | GSE178383 | GEO

Comparison between matched microdissected and whole tissue breast cancer specimen

Project description:A total of 38 flash-frozen breast cancer tissues were collected from three medical centers in the Netherlands (i.e. National Cancer institute: n=19; Radboud University Medical Center: n=4; Erasmus University Medical Center: n=15). All tissues were analyzed as laser capture microdissected (LCM) and whole samples (whole tissue lysate: WTL). All gathered samples were primary estrogen receptor (ER) tumors, which were subdivided in two patient groups according to outcome to first line (i.e. recurrent disease setting) tamoxifen therapy based on time-to-progression (TTP): patients which manifested progression of disease before (i.e. TTP <=) 6 months were defined as "poor outcome", while patients which manifested progression after (i.e. TTP>) 6 months were defined as "good outcome". All patients did not receive adjuvant hormonal therapy (i.e. tamoxifen or aromatase inhibitors post-surgical resection of primary tumor). The LCM subset derives from PXD000484 (Erasmus Medical Center samples) and PXD000485 (National Cancer Institute and Radboud University Medical Center).

2016-03-31 | PXD002381 | Pride

Expression data from intestine of HDAC1 and HDAC2 conditionally mutated mice

Project description:Acetylation and deacetylation of histones and other proteins depend on the opposing activities of histone acetyltransferases and histone deacetylases (HDACs), leading to either positive or negative gene expression changes. The use of HDAC inhibitors (HDACi) has uncovered a role for HDACs in the control of proliferation, apoptosis and inflammation. However, little is known of the roles of specific HDACs in intestinal epithelial cells (IEC). We investigated the consequences of ablating both Hdac1 and Hdac2 in murine IECs gene expression. HDAC1 and HDAC2 conditionally mutated mice were provided by Dr EN Olson (University of Texas Southwestern Medical Center, Dallas, TX) (Montgomery et al., 2007). Floxed HDAC1 and HDAC2 mice were crossed with villin-Cre transgenic mice to insure specific intestinal epithelial cell gene deletion (Madison et al., 2002).

2013-06-08 | GSE47745 | GEO

Genetic profiling to predict recurrence of early cervical cancer

Project description:We compared the prediction powers for disease recurrence between gene set prognostic model and clinical prognostic model developed in a single large population to see whether genetic quantitative approach will have significant prognostic role in early cervical cancer patients who underwent radical hysterectomy with or without adjuvant therapies. Gene set model to predict disease free survival of early cervical cancer was developed using DASL assay dataset from the cohort of early cervical cancer patients who were treated with radical surgery with or without adjuvant therapies at the Samsung Medical Center of Sungkyunkwan University School of Medicine in Seoul, Korea, between January 2002 and September 2008. Clinical prediction model was also developed in the same cohort and the ability of predicting recurrence from each model was compared.

2013-05-01 | GSE44001 | GEO

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