Project description:BACKGROUND: Dendritic cells (DC) play a central role in primary immune responses and become potent stimulators of the adaptive immune response after undergoing the critical process of maturation. Understanding the dynamics of DC maturation would provide key insights into this important process. Time course microarray experiments can provide unique insights into DC maturation dynamics. Replicate experiments are necessary to address the issues of experimental and biological variability. Statistical methods and averaging are often used to identify significant signals. Here a novel strategy for filtering of replicate time course microarray data, which identifies consistent signals between the replicates, is presented and applied to a DC time course microarray experiment. RESULTS: The temporal dynamics of DC maturation were studied by stimulating DC with poly(I:C) and following gene expression at 5 time points from 1 to 24 hours. The novel filtering strategy uses standard statistical and fold change techniques, along with the consistency of replicate temporal profiles, to identify those differentially expressed genes that were consistent in two biological replicate experiments. To address the issue of cluster reproducibility a consensus clustering method, which identifies clusters of genes whose expression varies consistently between replicates, was also developed and applied. Analysis of the resulting clusters revealed many known and novel characteristics of DC maturation, such as the up-regulation of specific immune response pathways. Intriguingly, more genes were down-regulated than up-regulated. Results identify a more comprehensive program of down-regulation, including many genes involved in protein synthesis, metabolism, and housekeeping needed for maintenance of cellular integrity and metabolism. CONCLUSIONS: The new filtering strategy emphasizes the importance of consistent and reproducible results when analyzing microarray data and utilizes consistency between replicate experiments as a criterion in both feature selection and clustering, without averaging or otherwise combining replicate data. Observation of a significant down-regulation program during DC maturation indicates that DC are preparing for cell death and provides a path to better understand the process. This new filtering strategy can be adapted for use in analyzing other large-scale time course data sets with replicates.

Project description:BACKGROUND: Dendritic cells (DC) play a central role in primary immune responses and become potent stimulators of the adaptive immune response after undergoing the critical process of maturation. Understanding the dynamics of DC maturation would provide key insights into this important process. Time course microarray experiments can provide unique insights into DC maturation dynamics. Replicate experiments are necessary to address the issues of experimental and biological variability. Statistical methods and averaging are often used to identify significant signals. Here a novel strategy for filtering of replicate time course microarray data, which identifies consistent signals between the replicates, is presented and applied to a DC time course microarray experiment. RESULTS: The temporal dynamics of DC maturation were studied by stimulating DC with poly(I:C) and following gene expression at 5 time points from 1 to 24 hours. The novel filtering strategy uses standard statistical and fold change techniques, along with the consistency of replicate temporal profiles, to identify those differentially expressed genes that were consistent in two biological replicate experiments. To address the issue of cluster reproducibility a consensus clustering method, which identifies clusters of genes whose expression varies consistently between replicates, was also developed and applied. Analysis of the resulting clusters revealed many known and novel characteristics of DC maturation, such as the up-regulation of specific immune response pathways. Intriguingly, more genes were down-regulated than up-regulated. Results identify a more comprehensive program of down-regulation, including many genes involved in protein synthesis, metabolism, and housekeeping needed for maintenance of cellular integrity and metabolism. CONCLUSIONS: The new filtering strategy emphasizes the importance of consistent and reproducible results when analyzing microarray data and utilizes consistency between replicate experiments as a criterion in both feature selection and clustering, without averaging or otherwise combining replicate data. Observation of a significant down-regulation program during DC maturation indicates that DC are preparing for cell death and provides a path to better understand the process. This new filtering strategy can be adapted for use in analyzing other large-scale time course data sets with replicates. DC were generated from the bone marrow of C57BL/6 mice using GM-CSF, Treated with poly I:C, and RNA was isolated at 0, 1, 3, 6, 12 and 24 hours, and subjected to microarray analysis. Two independent replicate experiments were performed.

Project description:Background: It has been shown that intracellular pathogens hijack DC functions to evade immune defense mechanisms. In this study, we investigated the responses of human monocyte derived DCs to four intracellular bacteria, Tropheryma whipplei, Coxiella burnetii, Brucella abortus and Orientia tsutsugamushi, responsible for human infectious diseases and known to infect myeloid cells. Methods: Whole genome microarrays were assessed to define common and specific transcriptionnal responses to bacterial pathogen. Bacterial pathogen ability to affect DC maturation was assessed by measuring lymphoproliferation and endocytosis as well as phenotypic maturation markers (CD80, CD83, CD86 and HLA-DR) expression. Results: We found that Coxiella burnetii, Orientia tsutsugamushi and Brucella abortus induced DC maturation assessed through decreased endocytosis ability, triggering lymphoproliferation, surface expression of HLA class II molecules and phenotypic changes, whereas Tropheryma whipplei did not induce DC maturation. As revealed by microarray analysis, the response of DCs to these bacteria consisted of a core associated with the maturation of DCs and signatures specific for each pathogen. The core response represented 10% of genes modulated in response to pathogens and consisted of general cellular processes including nucleotide binding, protein transport, cell fraction, protein kinase, cell cycle, mitochondrial membrane and cytoskeleton. The specific transcriptional signature induced by C. burnetii is associated with the communication between innate and adaptive immune cells and DC maturation. B. abortus signature specifically involved arachidonic acid and lipooxygenase pathways and O. tsutsugamushi signature involved type I and type III IFN responses. Conclusion: This study demonstrates that intracellular bacteria use multifaceted pathways to induce DC maturation which may lead to unadapted immune response. The understanding of these pathways may be useful to improve our knowledge of bacterial recognition by the immune system but also intracellular bacterial diseases.

Project description:Background: It has been shown that intracellular pathogens hijack DC functions to evade immune defense mechanisms. In this study, we investigated the responses of human monocyte derived DCs to four intracellular bacteria, Tropheryma whipplei, Coxiella burnetii, Brucella abortus and Orientia tsutsugamushi, responsible for human infectious diseases and known to infect myeloid cells. Methods: Whole genome microarrays were assessed to define common and specific transcriptionnal responses to bacterial pathogen. Bacterial pathogen ability to affect DC maturation was assessed by measuring lymphoproliferation and endocytosis as well as phenotypic maturation markers (CD80, CD83, CD86 and HLA-DR) expression. Results: We found that Coxiella burnetii, Orientia tsutsugamushi and Brucella abortus induced DC maturation assessed through decreased endocytosis ability, triggering lymphoproliferation, surface expression of HLA class II molecules and phenotypic changes, whereas Tropheryma whipplei did not induce DC maturation. As revealed by microarray analysis, the response of DCs to these bacteria consisted of a core associated with the maturation of DCs and signatures specific for each pathogen. The core response represented 10% of genes modulated in response to pathogens and consisted of general cellular processes including nucleotide binding, protein transport, cell fraction, protein kinase, cell cycle, mitochondrial membrane and cytoskeleton. The specific transcriptional signature induced by C. burnetii is associated with the communication between innate and adaptive immune cells and DC maturation. B. abortus signature specifically involved arachidonic acid and lipooxygenase pathways and O. tsutsugamushi signature involved type I and type III IFN responses. Conclusion: This study demonstrates that intracellular bacteria use multifaceted pathways to induce DC maturation which may lead to unadapted immune response. The understanding of these pathways may be useful to improve our knowledge of bacterial recognition by the immune system but also intracellular bacterial diseases. IL4/GM-CSF monocyte-derived dendritic cells were stimulated by T. whipplei, B. abortus, C. burnetii, O. tsutsugamushi and LPS during 6 hours. Common and specific signatures were determined by comparison with uninfected DCs. moDCs (5.10^6) were plated in 6 well plates and stimulated with bacteria or LPS for 6 hours, and total RNA was extracted using the RNeasy minikit (Qiagen, adresse CA) and DNase treatment. The Agilent-014850 4X44k Human Whole Genome microarrays (Agilent Technologies, CA) representing 44,000 probes were used as recently described. Reverse transcription, sample labeling and hybridization were performed according to protocols specified by the manufacturer (One-Color Microarray-Based Gene Expression Analysis). Three samples per experimental condition were included in the analysis.

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Overexpression of NF110b and NF110bΔDZF in Monocyte-Derived Dendritic Cells

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