Gene Expression Profiles of HLA-G1 Overexpressed in hES Cells

The goals of this study were to analyze the change in the global gene expression profile of exogenous human leukocyte antigen-G1 (HLA-G1) overexpressed in human embryonic stem (hES) cells and to explore the molecular mechanism by which the overexpression of HLA-G1 modifies immunologic pathways. Microarray and quantitative real-time PCR analyses were performed to quantify the differential expression pattern of HLA-G1?+?H1 hES cells. The results showed that HLA-G1 differentially regulated the expression of 425 genes with at least a twofold increase or decrease. These differentially expressed genes were classified into 13 functional groups, including cellular components, biological processes, and molecular functions. The pathways of focal adhesion, the TGF-β signaling pathway, and the immune response were the most predominantly affected. The synergism of these genes could explain the mechanism of the immunosuppression of HLA-G1?+?H1 hES cells. Thus, the expression pattern reflected a broad spectrum of roles of HLA-G1 in hES cells.     

Cross-Platform Prediction of Gene Expression Signatures

Gene expression signatures can predict the activation of oncogenic pathways and other phenotypes of interest via quantitative models that combine the expression levels of multiple genes. However, as the number of platforms to measure genome-wide gene expression proliferates, there is an increasing need to develop models that can be ported across diverse platforms. Because of the range of technologies that measure gene expression, the resulting signal values can vary greatly. To understand how this variation can affect the prediction of gene expression signatures, we have investigated the ability of gene expression signatures to predict pathway activation across Affymetrix and Illumina microarrays. We hybridized the same RNA samples to both platforms and compared the resultant gene expression readings, as well as the signature predictions. Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated. This demonstrates that our method can map probes from Affymetrix and Illumina microarrays, and that this mapping can be used to predict gene expression signatures across platforms.     

Gene Expression Profiles of Human Dendritic Cells Interacting with Aspergillus fumigatus in a Bilayer Model of the Alveolar Epithelium/Endothelium Interface

The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549) and endothelium (human pulmonary artery epithelial cells, HPAEC) on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC), monocyte-derived DC (moDC) and myeloid DC (mDC), were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA.     

MicroRNA 122对肝癌细胞基因表达谱的影响

为研究microRNA（miR-122）对肝癌细胞Hep3B基因表达谱的影响,并探讨其在肝癌发过程中的可能作用,构建了miR-122稳定高表达的Hep3B细胞,利用基因表达谱芯片技术筛选得到和对照组细胞比较的差异表达基因.研究结果显示,2倍以上变化的差异表达基因有490个,其中上调的有345个,下调的有145个.这些基因中有16个与肿瘤发生相关,其它基因涉及细胞周期、信号转导、细胞凋亡和细胞增殖分化等众多生物学过程.这些结果提示,miR-122可能在肝癌发生的过程中发挥作用,并可能与这些差异表达基因密切相关.另外,还结合生物信息学方法,在下调表达的基因中预测了miR-122可能直接作用的靶基因.本研究初步探讨了miR-122在肝癌细胞中的生物学功能,为进一步研究miR-122在肝癌发生中的作用奠定了基础,同时也为miRNA的生物学功能及其作用机制的研究提供了一些参考.     

High Throughput Screening of Gene Expression Signatures

This paper focuses on microarray image analysis and discusses a completely automated approach to image processing, which eliminates human intervention. A system for automated image processing is described, which is capable of processing image files in a batch-mode thus allowing high-throughput of microarray image analysis. Grid-placement and spot finding are achieved without operator's help. The software eliminates noise signals from the data analysis process and minimizes operator's involvement in the procedure.     

5-氟尿嘧啶敏感与非敏感的人胃癌BGC-823细胞基因表达谱差异分析

利用化疗药物5-氟尿嘧啶(5-Fu)对胃癌细胞株进行筛选和诱导,建立具有耐药性的胃癌细胞株.与亲代细胞株对比生长特性及基因表达谱,初步探讨胃癌细胞的耐药机制.采用四唑盐比色法(MTT)测定5-Fu对胃癌细胞株BGC-823的半数抑制浓度(IC50);根据IC50设计5-Fu剂量,用大剂量的5-Fu逐渐递增间歇给药的方法,反复筛选,获得5株胃癌耐药细胞株.比较耐药细胞株和亲本细胞株的形态和生长特性,继而再用人类肿瘤基因芯片(human cancer arrays)比较测试亲本与耐药细胞株的基因表达谱差异;对其中189个上调基因和133个下调基因采用Gene Ontology中的BP(Biological Process)分析这些基因相关的功能,并用MAS2.0分析这些基因可能涉及的信号通路.结果提示,胃癌细胞株耐药(5-Fu)相关基因可能与转录因子信号转导、TNF受体介导的细胞凋亡和抗凋亡、细胞周期调节、细胞粘附及MAP激酶类的功能相关.对细胞周期、信号转导相关的6个基因采用定量PCR验证,结果与基因表达芯片结果一致.上述结果有利于进一步发现胃癌细胞的耐药基因和相关信号通路,探索抗胃癌治疗的耐药机制.     

Linking Transcriptional Changes over Time in Stimulated Dendritic Cells to Identify Gene Networks Activated during the Innate Immune Response

The innate immune response is primarily mediated by the Toll-like receptors functioning through the MyD88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time-course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit α in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the MyD88-dependent and TRIF-dependent pathways in the innate immune response, time-course gene expression profiles from MyD88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88-dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the innate immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene sub-networks in other biological systems.     

Variation in Gene Expression of Inflammatory Cytokines in Leukocyte-Derived Cells of High-Fat-Diet-Induced Insulin-Resistant Rats

A high-fat diet is thought to enhance inflammation in various tissues by increasing insulin resistance. In this study, we determined the mRNA levels of inflammatory cytokines in leukocyte-derived cells in the blood of rats with high-fat-diet-induced insulin resistance. Feeding rats a high-fat diet for 77 d induced moderate insulin resistance, which was determined by increased plasma glucose and insulin concentrations, following an oral glucose tolerance test. The interleukin (IL)-1β mRNA level was higher in the insulin-resistant rats than in control rats at the fasting stage, whereas the tumor necrosis factor (TNF)-α mRNA level was greatly elevated at 180 min after glucose administration in the insulin-resistant rats. The results suggest that feeding rats a high-fat diet enhances the expression of fasting IL-1β and postprandial TNF-α genes in leukocyte-derived cells.     

表达谱基因芯片

表达谱基因芯片具有高通量、缩微、多参数、平行化等优点.在功能基因组学研究中正发挥越来越重要的作用.就其原理、应用、存在问题及解决策略等进行了综述.     

Self-Glycolipids Modulate Dendritic Cells Changing the Cytokine Profiles of Committed Autoreactive T Cells

The impact of glycolipids of non-mammalian origin on autoimmune inflammation has become widely recognized. Here we report that the naturally occurring mammalian glycolipids, sulfatide and β-GalCer, affect the differentiation and the quality of antigen presentation by monocyte-derived dendritic cells (DCs). In response to sulfatide and β-GalCer, monocytes develop into immature DCs with higher expression of HLA-DR and CD86 but lower expression of CD80, CD40 and CD1a and lower production of IL-12 compared to non-modulated DCs. Self-glycolipid-modulated DCs responded to lipopolysaccharide (LPS) by changing phenotype but preserved low IL-12 production. Sulfatide, in particular, reduced the capacity of DCs to stimulate autoreactive Glutamic Acid Decarboxylase (GAD65) - specific T cell response and promoted IL-10 production by the GAD65-specific clone. Since sulfatide and β-GalCer induced toll-like receptor (TLR)-mediated signaling, we hypothesize that self-glycolipids deliver a (tolerogenic) polarizing signal to differentiating DCs, facilitating the maintenance of self-tolerance under proinflammatory conditions.     

Gene Expression Analysis of Peripheral Cells for Subclassification of Pediatric Inflammatory Bowel Disease in Remission

Objective

In current clinical practice, optimal treatment of inflammatory bowel disease (IBD) aims at the induction and maintenance of clinical remission. Clinical remission is apparent when laboratory markers of inflammation are normal and clinical symptoms are absent. However, sub-clinical inflammation can still be present. A detailed analysis of the immune status during this inactive state of disease may provide a useful tool to categorize patients with clinical remission into subsets with variable states of immune activation.

Design

By using Affymetrix GeneChips, we analysed RNA gene expression profiles of peripheral blood leukocytes from pediatric IBD patients in clinical remission and controls. We performed (un)supervised clustering analysis of IBD-associated genes and applied Ingenuity® pathway software to identify specific molecular profiles between patients.

Results

Pediatric IBD patients with disease in clinical remission display heterogeneously distributed gene expression profiles that are significantly distinct from controls. We identified three clusters of IBD patients, each displaying specific expression profiles of IBD-associated genes.

Conclusion

The expression of immune- and IBD-associated genes in peripheral blood leukocytes from pediatric IBD patients in clinical remission was different from healthy controls, indicating that sub-clinical immune mechanisms are still active during remission. As such, RNA profiling of peripheral blood may allow for non-invasive patient subclassification and new perspectives in treatment regimes of IBD patients in the future.     

Identification of Common Prognostic Gene Expression Signatures with Biological Meanings from Microarray Gene Expression Datasets

Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.     

Molecular Signatures Identify a Candidate Target of Balancing Selection in an arcD-Like Gene of Staphylococcus epidermidis

A comparative population genetics study revealed high levels of nucleotide polymorphism and intermediate-frequency alleles in an arcC gene of Staphylococcus epidermidis, but not in a homologous gene of the more aggressive human pathogen, Staphylococcus aureus. Further investigation showed that the arcC genes used in the multilocus sequence typing schemes of these two species were paralogs. Phylogenetic analyses of arcC-containing loci, including the arginine catabolic mobile element, from both species, suggested that these loci had an eventful history involving gene duplications, rearrangements, deletions, and horizontal transfers. The peak signatures in the polymorphic S. epidermidis locus were traced to an arcD-like gene adjacent to arcC; these signatures consisted of unusually elevated Tajima’s D and π/K ratios, which were robust to assumptions about recombination and species divergence time and among the most elevated in the S. epidermidis genome. Amino acid polymorphisms, including one that differed in polarity and hydropathy, were located in the peak signatures and defined two allelic lineages. Recombination events were detected between these allelic lineages and potential donors and recipients of S. epidermidis were identified in each case. By comparison, the orthologous gene of S. aureus showed no unusual signatures. The ArcD-like protein belonged to the unknown ion transporter 3 family and appeared to be unrelated to ArcD from the arginine deiminase pathway. These studies report the first comparative population genetics results for staphylococci and the first statistical evidence for a candidate target of balancing selection in S. epidermidis.