Microarray analysis of B-cell stimulation

Proteomic changes during B cell maturation: 2D-DIGE approach

B cells play a pivotal role in adaptive immune system, since they maintain a delicate balance between recognition and clearance of foreign pathogens and tolerance to self. During maturation, B cells progress through a series of developmental stages defined by specific phenotypic surface markers and the rearrangement and expression of immunoglobulin (Ig) genes. To get insight into B cell proteome during the maturation pathway, we studied differential protein expression in eight human cell lines, which cover four distinctive developmental stages; early pre-B, pre-B, plasma cell and immature B cell upon anti-IgM stimulation. Our two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry based proteomic study indicates the involvement of large number of proteins with various functions. Notably, proteins related to cytoskeleton were relatively highly expressed in early pre-B and pre-B cells, whereas plasma cell proteome contained endoplasmic reticulum and Golgi system proteins. Our long time series analysis in anti-IgM stimulated Ramos B cells revealed the dynamic regulation of cytoskeleton organization, gene expression and metabolic pathways, among others. The findings are related to cellular processes in B cells and are discussed in relation to experimental information for the proteins and pathways they are involved in. Representative 2D-DIGE maps of different B cell maturation stages are available online at http://structure.bmc.lu.se/BcellProteome/.

Dynamic covariation between gene expression and genome characteristics

Gene and protein expression is controlled so that cells can react to changing intra- and extracellular signals by modulating biochemical networks and pathways. We have previously shown that gene expression and the properties of expressed proteins are dynamically correlated. Here we investigated correlations between gene related parameters and gene expression patterns, and found statistically significant correlations in microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, cell cycle in HeLa cells, infection in intestinal epithelial cells, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Our method was applied to time course datasets individually for each time point. We derived from sequence information numerous parameters for nucleotide composition, two-base composition, codon usage, skew parameters, and codon bias. In addition to coding regions, we also investigated correlations for complete genes and introns. Significant dynamic correlations were identified for each of the analyses. Our method also proved useful for detecting dynamic shifts in gene expression profiles, such as in the D. melanogaster dataset. Detection of changes in the properties of expressed genes and proteins might be useful for predicting or following biological processes, responses, growth, differentiation and possibly in related disorders.

Immunological systems biology: Gene expression analysis of B-cell development in Ramos B-cells

B-cell development into antibody producing cells is a complex process that relies on the tightly controlled production of hundreds of genes and proteins. A B-cell is activated through the B-cell receptor (BCR) and this activation is modified by different co-stimulatory or inhibitory co-receptors. The concerted action of signals from BCR and from co-receptors decides the fate of the B-cells. The majority of B-cells enter apoptosis, while some of them progress through the cell cycle and become, for example, antibody producing plasma cells. We studied BCR stimulated Ramos B-cells to explore the expression of BCR pathway, cell cycle and apoptosis related genes. We followed, using microarrays, the gene expression for several days after BCR engagement. Several bioinformatics methods were used to investigate the properties and common features of co-expressed genes. Certain gene ontologies have statistically significant enrichment into clusters of similarly expressed genes. The cell signaling pathways and gene expression data were combined to reveal detailed information about biological processes and B-cell systems biology. The results provide knowledge of the development of adaptive immunity and clues about how the pathways are affected by regulation of the expression of genes.

Proteome analysis of B-cell maturation

Proteins affected by anti-mIgM stimulation during B-cell maturation were identified using 2-DE-based proteomics. We investigated the proteome profiles of stimulated and nonstimulated Ramos B-cells at eight time points during 5 d and compared the obtained proteomic data to the corresponding data from DNA-microarray studies. Anti-mIgM stimulation of the cells resulted in significant differences (> or =twofold) in the protein abundance close to 100 proteins and differences in post-translational protein modifications. Forty-eight up- or down-regulated proteins were identified by mass spectrometric methods and database searches. The identities of a further nine proteins were revealed by comparing their positions to the known proteins in other lymphocyte 2-DE databases. Several of the proteins are directly related to the functional and morphological characteristics of B-cells, such as cytoskeleton rearrangement and intracellular signalling triggered by the crosslinking of B-cell receptors. In addition to proteins known to be involved in human B-cell maturation, we identified several proteins that were not previously linked to lymphocyte differentiation. The results provide deeper insights into the process of B-cell maturation and may lead to novel therapeutic strategies for immunodeficiencies. An interactive 2-DE reference map is available at http://bioinf.uta.fi/BcellProteome.

Microarray analysis of the differential effects of open and laparoscopic surgery on murine splenic T-cells

BACKGROUND

Surgical trauma depresses cell-mediated immunity of a duration and magnitude proportional to the degree of injury. However, the cellular mechanism underlying this effect is poorly understood. Microarrays were used to survey gene expression in murine splenic T-cells after pneumoperitoneum and laparotomy.

METHODS

C3H/HeJ mice were assigned randomly to undergo anesthesia alone, sham laparotomy, or CO(2) pneumoperitoneum and sacrificed 12 or 24 hours later. RNA was isolated from purified splenic T-cells and hybridized to Affymetrix oligonucleotide microarrays.

RESULTS

Relative to anesthesia, 116 genes after pneumoperitoneum and 398 genes after laparotomy showed a > or =2-fold change in expression at 12 hours. One hundred thirty-two genes after pneumoperitoneum and 157 genes after laparotomy met those criteria at 24 hours. Comparing surgical modalities, 177 genes were increased and 15 decreased > or =2-fold after laparotomy relative to pneumoperitoneum at 12 hours, compared with 44 and 5 genes respectively at 24 hours. Expression changes for 8 genes were validated by quantitative real-time polymerase chain reaction.

CONCLUSIONS

Laparotomy and pneumoperitoneum alter splenic T-cell gene expression, with the most extensive changes occurring 12 hours after laparotomy. This study is one of the first comprehensive genomic studies of the molecular effects of surgical manipulation on immune function. The genes identified are potential targets for modulating the immune response to surgery.

Dynamic covariation between gene expression and proteome characteristics

Background

Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Since the majority of genes encode proteins, we investigated possible correlations between protein parameters and gene expression patterns to identify proteome-wide characteristics indicative of trends common to expressed proteins.

Results

Numerous bioinformatics methods were used to filter and merge information regarding gene and protein annotations. A new statistical time point-oriented analysis was developed for the study of dynamic correlations in large time series data. The method was applied to investigate microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle.

Conclusion

We show that the properties of proteins synthesized correlate dynamically with the gene expression profile, indicating that not only is the actual identity and function of expressed proteins important for cellular responses but that several physicochemical and other protein properties correlate with gene expression as well. Gene expression correlates strongly with amino acid composition, composition- and sequence-derived variables, functional, structural, localization and gene ontology parameters. Thus, our results suggest that a dynamic relationship exists between proteome properties and gene expression in many biological systems, and therefore this relationship is fundamental to understanding cellular mechanisms in health and disease.

Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data

Immune cell-specific expression is one indication of the importance of a gene's role in the immune response. We have compiled a compendium of microarray expression data for virtually all human genes from six key immune cell types and their activated and differentiated states. Immune Response In Silico (IRIS) is a collection of genes that have been selected for specific expression in immune cells. The expression pattern of IRIS genes recapitulates the phylogeny of immune cells in terms of the lineages of their differentiation. Gene Ontology assignments for IRIS genes reveal significant involvement in inflammation and immunity. Genes encoding CD antigens, cytokines, integrins and many other gene families playing key roles in the immune response are highly represented. IRIS also includes proteins of unknown function and expressed sequence tags that may not represent genes. The predicted cellular localization of IRIS proteins is evenly distributed between cell surface and intracellular compartments, indicating that immune specificity is important at many points in the signaling pathways of the immune response. IRIS provides a resource for further investigation into the function of the immune system and immune diseases.

Tracking gene expression in primary immunodeficiencies

PURPOSE OF REVIEW

Extensive research on molecular genetics in recent decades has provided a wealth of information about the mechanisms of primary immunodeficiency diseases. Microarray technology enables the survey of the expression of thousands of genes simultaneously. This review focuses on the commonly used arrays and initial applications in the study of primary immunodeficiency diseases. The application of this technology has been found to accelerate the discovery rate of gene expression disturbances in primary immunodeficiency diseases and provide potential molecular diagnostic tools.

RECENT FINDINGS

The important role of microarray technology in functional genomic study has been demonstrated by the exponential growth in the number of scientific publications in the last few years. Microarray analysis has been used to study gene expression in several immunodeficiency diseases with known gene mutations as well as those with unknown causes. It has provided snapshots of gene expression and has presented the molecular phenotypes in the cells at defined times and under certain stimulation conditions. Studies comparing differential gene expression in patients and normal controls have allowed us to better understand the immunodeficiencies at the molecular level.

SUMMARY

Application of microarray technology in immunodeficiency study has facilitated tracking the expression of thousands of genes simultaneously. The molecular phenotypes obtained from microarray results can be used in diagnosis of diseases, supplemental to clinical phenotypes. It is a powerful survey tool that can detect disturbed gene expression in immunodeficiency diseases, which will provide clues for disease gene discovery and potential targets for drug development.

Stimulation-induced gene expression in Ramos B-cells

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 ( approximately 1,500) 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.