Stimulation-induced gene expression in Ramos B-cells

Abstract

The development of adaptive immunity and responses to foreign molecules and organisms relies on the highly regulated production of hundreds of proteins. B-cell maturation, from committed progenitors to terminally differentiated plasma cells, is a multistep process that requires the ordered expression of a large number of genes. We studied anti-IgM-stimulated Ramos cells to explore genome-wide expression patterns in differentiating human B-cells. cDNA microarrays were used to measure changes in transcript levels over several days. A large set of genes (B1500) showed significantly altered expression at one or more time points. The expression profiles were used to construct gene clusters that were then characterized further with respect to the functions of the encoded proteins. Several groups of genes relevant to B-cells were analyzed in detail including early response genes and genes related to transcription, apoptosis and cell cycle regulation. Extensive bioinformatics analyses were conducted to identify the genes/proteins and to study functions and pathways involving B-cells. The results pave the way for understanding the development of humoral immunity, and provide new candidate genes and targets for research and drug development.

Human Transcriptional Coactivator PC4 Stimulates DNA End Joining and Activates DSB Repair Activity

“…The envisaged role of PC4 in V(D)J recombination is supported by a microarray analysis of Ramos-B cells stimulated with anti-IgM. 30 It was found that PC4 expression upregulated in 24 h upon stimulation. This may further indicate the role of PC4 in NHEJ, which is part of V(D)J recombination.…”

Dynamic covariation between gene expression and genome characteristics

“…Our GExCo (Gene Expression Correlation) analysis method is based on Spearman linear correlation to monitor covariations between a number of gene parameters and gene expression levels along a time series. Similarly to the protein characteristics study (Sharabiani et al, 2005), clear correlations were evident for all the studied experiments, which contain high-quality datasets for human T cell stimulation (Diehn et al, 2002) and B cell stimulation (Ollila and Vihinen, 2002;Ollila and Vihinen, 2003), innate immune response to infection by L. monocytogenes (Baldwin et al, 2003), human (Whitfield et al, 2002) and yeast cell cycle data (Spellman et al, 1998), and D. melanogaster life cycle data (Arbeitman et al, 2002).…”

“…In total, 4359 cDNA elements (of approximately 18,000 genes and ESTs on the chip) representing 2240 genes were significantly altered after CD3 stimulation or CD3/CD28 costimulation (Diehn et al, 2002). The B cell dataset for genes involved in maturation in anti-immunoglobulin M-stimulated Ramos cells indicated that 1268 genes had significantly altered expression, at least at one time point (Ollila and Vihinen, 2002;Ollila and Vihinen, 2003).…”

“…The B cell dataset (Ollila and Vihinen, 2002;Ollila and Vihinen, 2003) is for genes involved in maturation in antiimmunoglobulin M-stimulated Ramos cells. The development of adaptive immunity and responses to foreign organisms and molecules is based on the finely regulated production of hundreds of proteins.…”

Dynamic covariation between gene expression and proteome characteristics

“…We observed very significant and dynamic correlations in all the datasets we investigated. We investigated several high-quality datasets for different cell types, treatments, and organisms, including human T cell stimulation [20] and B cell stimulation datasets [8,21], yeast cell cycle data [22], and Drosophila melanogaster life cycle data [23]. …”