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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Identification of translationally deregulated proteins during inflammation

ABSTRACT: The regulation of translation is crucial for cells to rapidly adapt to changing conditions. Although the transcriptional changes under inflammatory conditions are intensely studied, not much is known about translational changes. Therefore, this study aimed at identifying translationally deregulated targets in inflammatory settings. MCF-7 cells were treated for 4h with the supernatants of U937 monocytes or TPA-activated U937 monocyte-derived macrophages and subjected to polysomal fractionation using sucrose gradients. Total RNA was collected simultaneously.

ORGANISM(S): Homo sapiens

SUBMITTER: Tobias Schmid

PROVIDER: E-GEOD-35022 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Identification of translationally deregulated proteins during inflammation

Project description:The regulation of translation is crucial for cells to rapidly adapt to changing conditions. Although the transcriptional changes under inflammatory conditions are intensely studied, not much is known about translational changes. Therefore, this study aimed at identifying translationally deregulated targets in inflammatory settings.

2012-08-01 | GSE35022 | GEO

U937 cells: differentiating vs. undifferentiated

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2010-06-20 | E-GEOD-10560 | biostudies-arrayexpress

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Project description:Gene-expression changes in U937 cells undergoing monocytic differentiation with TPA treatment Keywords: differentiation treatment

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B27 modulation of LPS response

Project description:Objectives How HLA-B27 contributes towards arthritis susceptibility is still unclear, but effects on the response to bacteria unrelated to the classical antigen presenting role of B27 have been suggested. This study investigated whether HLA-B27 modulates the innate response to LPS, a component shared between all Gram –ve bacteria that can trigger reactive arthritis. Methods Pools of U937 transfectants expressing either HLA-B27, HLA-A2, or the expression plasmid alone were differentiated with PMA and stimulated with LPS. Supernatants were analysed for TNF-alpha secretion and the gene expression profiles of unstimulated and LPS stimulated cells were determined by microarray analysis. Changes in gene expression that are indicative of an unfolded protein response were also analysed by quantitative PCR. Results TNF-alpha secretion, a biological marker of the inflammatory response to LPS, was not significantly different between U937-B27 and U937-control. No differences in gene expression between unstimulated U937- B27 and U937-control lines were detected. Both U937-control and U937-B27 exhibited a stereotypic response to LPS. Only 1 gene, OAS2, was differentially expressed by these cell lines, and this was confirmed by quantitative PCR. Analysis of XBP-1 splicing suggested that a small increase in the unfolded protein response is induced following LPS stimulation, but this increase was seen in all transfectants. Conclusions The expression of B27 does not profoundly alter gene expression following LPS stimulation. Therefore, additional signals, such as those provided by cytokines or intracellular infection, may be required to reveal any influence of B27 expression on the inflammatory response. Keywords: antigen response

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RBP2 location analysis

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The midbody acts as a translationally active membraneless organelle

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Microarray profiling of monocytic differentiaion reveals miRNA-mRNA intrinsic correlation (gene expression)

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Assessing efficiency of single cell population by Drop-seq using cell mixture of epithelial and myeloid cells.

Project description:A lung epithelial cell line was mixed with monocytes/marcophages, and then cells were separated using specific antibodies and/or Drop-seq. PC9 is a non-small cell lung carcinoma (NSCLC) cell line. Myeloid lineage cell line U937 are known to differentiate along monocyte/marcophage lineage by TPA. Using Drop-seq, we were able to clearly distinguish PC9 from U937 cells in the mixture. The separation by Drop-seq was correlated with the separation by cell type-specific antibodies. We were able to identify specific biomarkers, as preferentially expressed genes, for each cell population. The results of our study addresses the quality of cell separation by Drop-seq.

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