Unique gene expression profiles of human macrophages and dendritic cells to phylogenetically distinct parasites

Blood ◽  
2003 ◽  
Vol 102 (2) ◽  
pp. 672-681 ◽  
Author(s):  
Damien Chaussabel ◽  
Roshanak Tolouei Semnani ◽  
Mary Ann McDowell ◽  
David Sacks ◽  
Alan Sher ◽  
...  

AbstractMonocyte-derived dendritic cells (DCs) and macrophages (Mϕs) generated in vitro from the same individual blood donors were exposed to 5 different pathogens, and gene expression profiles were assessed by microarray analysis. Responses to Mycobacterium tuberculosis and to phylogenetically distinct protozoan (Leishmania major, Leishmania donovani, Toxoplasma gondii) and helminth (Brugia malayi) parasites were examined, each of which produces chronic infections in humans yet vary considerably in the nature of the immune responses they trigger. In the absence of microbial stimulation, DCs and Mϕs constitutively expressed approximately 4000 genes, 96% of which were shared between the 2 cell types. In contrast, the genes altered transcriptionally in DCs and Mϕs following pathogen exposure were largely cell specific. Profiling of the gene expression data led to the identification of sets of tightly coregulated genes across all experimental conditions tested. A newly devised literature-based clustering algorithm enabled the identification of functionally and transcriptionally homogenous groups of genes. A comparison of the responses induced by the individual pathogens by means of this strategy revealed major differences in the functionally related gene profiles associated with each infectious agent. Although the intracellular pathogens induced responses clearly distinct from the extracellular B malayi, they each displayed a unique pattern of gene expression that would not necessarily be predicted on the basis of their phylogenetic relationship. The association of characteristic functional clusters with each infectious agent is consistent with the concept that antigen-presenting cells have prewired signaling patterns for use in the response to different pathogens.

2007 ◽  
Vol 76 (3) ◽  
pp. 1186-1192 ◽  
Author(s):  
David J. Gregory ◽  
Robert Sladek ◽  
Martin Olivier ◽  
Greg Matlashewski

ABSTRACT The intracellular parasite Leishmania causes a wide spectrum of human disease, ranging from self-resolving cutaneous lesions to fatal visceral disease, depending on the species of Leishmania involved. The mechanisms by which different Leishmania species cause different pathologies are largely unknown. We have addressed this question by comparing the gene expression profiles of bone marrow-derived macrophages infected with either Leishmania donovani or L. major promastigotes. We found that the two species had very similar effects on macrophage gene expression. Both species caused a small (<2.5-fold) but statistically significant repression of several hundred genes. In addition, both species strongly induced and repressed about 60 genes. Comparing the effects of the two species showed that only 26 genes were regulated differently by L. major as opposed to L. donovani, including those for metallothioneins 1 and 2, HSP70 and -72, CCL4, Gadd45β, Dsp1, matrix metalloprotease 13, T-cell death-associated gene 51 (Tdag51), RhoB, spermine/spermidine N1-acyl transferase 1 (SSAT), and Cox2. L. donovani-infected macrophages were also found to express higher levels of Cox2 protein and prostaglandin E synthase mRNA than L. major-infected macrophages. While both species have previously been shown to trigger prostaglandin E synthesis by bystander cells, this study suggests that infected macrophages themselves express prostaglandin E-synthesizing genes only in response to L. donovani.


2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


Autoimmunity ◽  
2015 ◽  
Vol 49 (2) ◽  
pp. 90-101 ◽  
Author(s):  
Eun Gae Lee ◽  
Nam-Chul Jung ◽  
Jun-Ho Lee ◽  
Jie-Young Song ◽  
Sang-Young Ryu ◽  
...  

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Pingzhang Wang ◽  
Yehong Yang ◽  
Wenling Han ◽  
Dalong Ma

Abstract Gene expression is highly dynamic and plastic. We present a new immunological database, ImmuSort. Unlike other gene expression databases, ImmuSort provides a convenient way to view global differential gene expression data across thousands of experimental conditions in immune cells. It enables electronic sorting, which is a bioinformatics process to retrieve cell states associated with specific experimental conditions that are mainly based on gene expression intensity. A comparison of gene expression profiles reveals other applications, such as the evaluation of immune cell biomarkers and cell subsets, identification of cell specific and/or disease-associated genes or transcripts, comparison of gene expression in different transcript variants and probe set quality evaluation. A plasticity score is introduced to measure gene plasticity. Average rank and marker evaluation scores are used to evaluate biomarkers. The current version includes 31 human and 17 mouse immune cell groups, comprising 10,422 and 3,929 microarrays derived from public databases, respectively. A total of 20,283 human and 20,963 mouse genes are available to query in the database. Examples show the distinct advantages of the database. The database URL is http://immusort.bjmu.edu.cn/.


2009 ◽  
Vol 26 (9) ◽  
pp. 1259-1274 ◽  
Author(s):  
François Trottein ◽  
Lana Schaffer ◽  
Stoyan Ivanov ◽  
Christophe Paget ◽  
Catherine Vendeville ◽  
...  

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