Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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

ABSTRACT: Since the expression profile of miRNAs is specific in different tissues or under different physiological conditions, the correlations between miRNAs and mRNAs could vary under different biological circumstances. This is a study also used expression profiles of miRNA and mRNA during monocytic differentiation to explore the correlations between the expression levels of miRNAs and mRNA, either negative or positive. After treatment of TPA, U937 cells present functional differentiation markers as well as specific cell morphology, which were confirmed by flow cytometric analysis and Wright-Giemsa staining.Here we use genome-wide microarray analysis to profile the expression levels of mRNA in normal U937 cells and differentiated U937 cells. For each differentiated and control sample, two hybridizations were performed by using a reversal fluorescent strategy.

ORGANISM(S): Homo sapiens

SUBMITTER: jing wang

PROVIDER: E-GEOD-26377 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Microarray profiling of monocytic differentiation reveals miRNA-mRNA intrinsic correlation.

Wang Jing J Xiang Guangxing G Mitchelson Keith K Zhou Yuxiang Y

Journal of cellular biochemistry 20110901 9

MiRNAs (microRNAs) are small non-coding RNAs involved in mammalian gene expression of cellular processes including differentiation, apoptosis and cancer development. Both specific miRNAs and mRNAs have been identified during monocytic differentiation, but their interactions have not been fully characterized. Here we report that by genome-wide microarray analysis for U937 monocytic differentiation induced by TPA, a large number of miRNAs and mRNAs were differentially expressed, and by bioinformat ...[more]

PMID: 21538479

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Project description:The potential for epigenetic changes in host cells following microbial infection has been widely suggested, but few examples have been reported. We assessed genome-wide patterns of DNA methylation in human macrophage-like U937 cells following infection with Burkholderia pseudomallei, an intracellular bacterial pathogen and the causative agent of human melioidosis. Our analyses revealed significant changes in host cell DNA methylation, at multiple CpG sites in the host cell genome, following infection. Infection induced differentially methylated probes (iDMPs) showing the greatest changes in DNA methylation were found to be in the vicinity of genes involved in inflammatory responses, intracellular signalling, apoptosis and pathogen-induced signalling. A comparison of our data with reported methylome changes in cells infected with M. tuberculosis revealed commonality of differentially methylated genes, including genes involved in T cell responses (BCL11B, FOXO1, KIF13B, PAWR, SOX4, SYK), actin cytoskeleton organisation (ACTR3, CDC42BPA, DTNBP1, FERMT2, PRKCZ, RAC1), and cytokine production (FOXP1, IRF8, MR1). Overall our findings show that pathogenic-specific and pathogen-common changes in the methylome occur following infection. The human leukemic monocyte lymphoma cell line (U937, ATCC CRL-1593.2) was maintained in RPMI 1640 supplemented with 10% foetal bovine serum (FBS) at 37Â°C. U937 cells were differentiated to macrophage-like cells following exposure to 20 ng/ml (final concentration) of phorbol 12-myristate 13-acetate (PMA) for 48 hours at 37Â°C and differentiation evidenced by increased adherence to tissue culture flasks. Overnight cultures of B. pseudomallei K96243 were diluted in L-15 medium and added to differentiated U937 cells at a multiplicity of infection (MOI) of 10. Uninfected controls were overlaid with L15 medium only. The cells were then incubated at 37Â°C to allow infection. The cells were washed 3 times with PBS and incubated with fresh L15 medium containing 1mg/ml kanamycin to kill extracellular bacteria. At appropriate time points the cells were washed 3 times in warm PBS and lysed with 0.1% (vol/vol) Triton X-100. DNA was isolated using an AllPrep kit (Qiagen) and stored at -80ÂºC until required. DNA yield was measured using a Nanodrop instrument with measurements between 22.8 â 50.6 ng/ul. Two experiments were carried out using the above procedure. In Experiment 1, DNA was collected from uninfected and infected cells at 2 hours (T2), and 4 hours (T4) post infection (2 biological replicates and 2 technical replicates from each group). In Experiment 2, DNA was collected from uninfected and infected cells at 1 hour (T1), 2 hours (T2), 3 hours (T3) and 4 hours (T4) post infection (1 sample from each group). The DNA methylation profile was determined using the Infinium HumanMethylation450 BeadChip (450K) (Illumina Inc.) following the manufacturerâs instructions. The data was extracted and the initial analysis was performed using GenomeStudio (2010.3) methylation module (1.8.5). Quality control checks and quantile normalisation were implemented using WateRmelon. Samples with more than 1% of sites with a detection p-value greater than 0.05 were removed as were probes with 1% of samples with a detection p-value greater than 0.05. Probes were removed if they had a bead count less than 3 in 1% of samples. Cross-hybridizing probes were removed, leaving 425496 probes for analysis. Here we report DNA methylation profile of 18 samples (10 infected and 8 control).

Dataset Information

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

Publications

Microarray profiling of monocytic differentiation reveals miRNA-mRNA intrinsic correlation.

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