Expander: from expression microarrays to networks and functions

Ulitsky, Igor; Maron‐Katz, Adi; Shavit, Sara; Sagir, Dorit; Linhart, Chaim; Elkon, Ran; Tanay, Amos; Sharan, Roded; Shiloh, Yosef; Shamir, Ron

doi:10.1038/nprot.2009.230

Cited by 180 publications

(160 citation statements)

References 62 publications

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“…The cutoff for the enrichment p value was set to 0.001. Transcription factor binding site (TFBS) enrichment was performed using the PRIMA algorithm (http://acgt.cs.tau.ac.il/prima/) (Elkon et al 2003) provided in the Expander software suite (version 6.04; 43 http://acgt.cs.tau.ac.il/expander/) (Ulitsky et al 2010), and the cutoff for the enrichment p value was set to 0.01.…”

Section: Download and Preprocessing Of Open Tg-gates Datamentioning

confidence: 99%

Toxicogenomics directory of chemically exposed human hepatocytes

et al. 2014

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A long-term goal of numerous research projects is to identify biomarkers for in vitro systems predicting toxicity in vivo. Often, transcriptomics data are used to identify candidates for further evaluation. However, a systematic directory summarizing key features of chemically influenced genes in human hepatocytes is not yet available. To bridge this gap, we used the Open TG-GATES database with Affymetrix files of cultivated human hepatocytes incubated with chemicals, further sets of gene array data with hepatocytes from human donors generated in this study, and publicly available genome-wide datasets of human liver tissue from patients with non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular cancer (HCC). After a curation procedure, expression data of 143 chemicals were included into a comprehensive biostatistical analysis. The results are summarized in the publicly available toxicotranscriptomics directory (http://wiki.toxbank.net/toxicogenomics-map/) which provides information for all genes whether they are up- or downregulated by chemicals and, if yes, by which compounds. The directory also informs about the following key features of chemically influenced genes: (1) Stereotypical stress response. When chemicals induce strong expression alterations, this usually includes a complex but highly reproducible pattern named 'stereotypical response.' On the other hand, more specific expression responses exist that are induced only by individual compounds or small numbers of compounds. The directory differentiates if the gene is part of the stereotypical stress response or if it represents a more specific reaction. (2) Liver disease-associated genes. Approximately 20 % of the genes influenced by chemicals are up- or downregulated, also in liver disease. Liver disease genes deregulated in cirrhosis, HCC, and NASH that overlap with genes of the aforementioned stereotypical chemical stress response include CYP3A7, normally expressed in fetal liver; the phase II metabolizing enzyme SULT1C2; ALDH8A1, known to generate the ligand of RXR, one of the master regulators of gene expression in the liver; and several genes involved in normal liver functions: CPS1, PCK1, SLC2A2, CYP8B1, CYP4A11, ABCA8, and ADH4. (3) Unstable baseline genes. The process of isolating and the cultivation of hepatocytes was sufficient to induce some stress leading to alterations in the expression of genes, the so-called unstable baseline genes. (4) Biological function. Although more than 2,000 genes are transcriptionally influenced by chemicals, they can be assigned to a relatively small group of biological functions, including energy and lipid metabolism, inflammation and immune response, protein modification, endogenous and xenobiotic metabolism, cytoskeletal organization, stress response, and DNA repair. In conclusion, the introduced toxicotranscriptomics directory offers a basis for a rationale choice of candidate genes for biomarker evaluation studies and represents an easy to use source of background information on chemically infl...

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Section: Download and Preprocessing Of Open Tg-gates Datamentioning

confidence: 99%

Toxicogenomics directory of chemically exposed human hepatocytes

et al. 2014

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“…We clustered the expression patterns of a selected set of genes using the CLICK algorithm from the software package Expander 5.0 using Pearson correlation as a distance measure (27). Log ratio data was imported in Expander, and probes were annotated using the gene mapping for Agilent WHG arrays available in Expander.…”

Section: Methodsmentioning

confidence: 99%

“…Averaging over all the probes mapped to the same gene revealed a dataset of 416 unique genes for us to further analyze. We clustered the expression patterns of these genes using the CLICK algorithm from the software package Expander 5.0 (27). Clustering detected 4 major trends describing the kinetics of the genes during HCMV infection.…”

Section: Overall Changes In Gene Expression Patterns To Measure Chanmentioning

confidence: 99%

Molecular profiling of cytomegalovirus-induced human CD8+ T cell differentiation

Hertoghs

Moerland

Stijn³

et al. 2010

J. Clin. Invest.

169

202

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“…A computational transcription factor (TF) analysis of differentially expressed genes in Timp3 2/2 M1 versus WT M1 BMDMs was performed, using Expander software (32). The enrichment of TFs was determined using a Bonferroni-adjusted P-value cutoff of less than 0.01.…”

Section: /2mentioning

confidence: 99%

Tissue Inhibitor of Metalloproteinases–3 Moderates the Proinflammatory Status of Macrophages

Gill

Gharib

Bench

et al. 2013

Am J Respir Cell Mol Biol

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Tissue inhibitor of metalloproteinases-3 (TIMP-3) has emerged as a key mediator of inflammation. Recently, we reported that the resolution of inflammation is impaired in Timp3 2/2 mice after bleomycininduced lung injury. Here, we demonstrate that after LPS instillation (another model of acute lung injury), Timp32/2 mice demonstrate enhanced and persistent neutrophilia, increased numbers of infiltrated macrophages, and delayed weight gain, compared with wild-type (WT) mice. Because macrophages possess broad immune functions and can differentiate into cells that either stimulate inflammation (M1 macrophages) or are immunosuppressive (M2 macrophages), we examined whether TIMP-3 influences macrophage polarization. Comparisons of the global gene expression of unstimulated or LPS-stimulated bone marrow-derived macrophages (BMDMs) from WT and Timp3 2/2 mice revealed that Timp3 2/2 BMDMs exhibited an increased expression of genes associated with proinflammatory (M1) macrophages, including Il6, Il12, Nos2, and Ccl2. Microarray analyses also revealed a baseline difference in gene expression between WT and Timp3 2/2 BMDMs, suggesting altered macrophage differentiation. Furthermore, the treatment of Timp3 2/2 BMDMs with recombinant TIMP-3 rescued this altered gene expression. We also examined macrophage function, and found that Timp3 2/2 M1 cells exhibit significantly more neutrophil chemotactic activity and significantly less soluble Fas ligand-induced caspase-3/7 activity, a marker of apoptosis, compared with WT M1 cells. Macrophage differentiation into immunosuppressive M2 cells is mediated by exposure to IL-4/IL-13, and we found that Timp3 2/2 M2 macrophages demonstrated a lower expression of genes associated with an anti-inflammatory phenotype, compared with WT M2 cells. Collectively, these findings indicate that TIMP-3 functions to moderate the differentiation of macrophages into proinflammatory (M1) cells.Keywords: resolution of inflammation; macrophage; metalloproteinase; lung injury Several immunosuppressive mechanisms have evolved to ensure that acute, generally beneficial inflammation does not progress to chronic, destructive inflammation. Beyond reversal of the initiating event (e.g., bacterial clearance and wound closure), active host processes, such as the release of the anti-inflammatory cytokines IL-4, IL-10, and IL-13, among other processes (1), actively repress the proinflammatory properties of various cell types. Macrophages, through their ability to clear neutrophils and release anti-inflammatory cytokines, are thought to be important in the resolution of inflammation (2).Generally speaking, macrophages are key effectors promoting the shift from a proinflammatory to an anti-inflammatory environment, and can be broadly classified into two groups: classically activated (M1) and alternatively activated (M2) macrophages, which can be further subdivided into specialized M2 groups (3). M1 macrophages are induced by proinflammatory Th1 cytokines, such as IFN-g, and are characterized by the production of proinfl...

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Expander: from expression microarrays to networks and functions

Cited by 180 publications

References 62 publications

Toxicogenomics directory of chemically exposed human hepatocytes

Toxicogenomics directory of chemically exposed human hepatocytes

Molecular profiling of cytomegalovirus-induced human CD8+ T cell differentiation

Tissue Inhibitor of Metalloproteinases–3 Moderates the Proinflammatory Status of Macrophages

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