548 research outputs found
Detection of Gene Expression in an Individual Cell Type within a Cell Mixture Using Microarray Analysis
BACKGROUND: A central issue in the design of microarray-based analysis of global gene expression is the choice between using cells of single type and a mixture of cells. This study quantified the proportion of lipopolysaccharide (LPS) induced differentially expressed monocyte genes that could be measured in peripheral blood mononuclear cells (PBMC), and determined the extent to which gene expression in the non-monocyte cell fraction diluted or obscured fold changes that could be detected in the cell mixture. METHODOLOGY/PRINCIPAL FINDINGS: Human PBMC were stimulated with LPS, and monocytes were then isolated by positive (Mono+) or negative (Mono-) selection. The non-monocyte cell fraction (MonoD) remaining after positive selection of monocytes was used to determine the effect of non-monocyte cells on overall expression. RNA from LPS-stimulated PBMC, Mono+, Mono- and MonoD samples was co-hybridised with unstimulated RNA for each cell type on oligonucleotide microarrays. There was a positive correlation in gene expression between PBMC and both Mono+ (0.77) and Mono- (0.61-0.67) samples. Analysis of individual genes that were differentially expressed in Mono+ and Mono- samples showed that the ability to detect expression of some genes was similar when analysing PBMC, but for others, differential expression was either not detected or changed in the opposite direction. As a result of the dilutional or obscuring effect of gene expression in non-monocyte cells, overall about half of the statistically significant LPS-induced changes in gene expression in monocytes were not detected in PBMC. However, 97% of genes with a four fold or greater change in expression in monocytes after LPS stimulation, and almost all (96-100%) of the top 100 most differentially expressed monocyte genes were detected in PBMC. CONCLUSIONS/SIGNIFICANCE: The effect of non-responding cells in a mixture dilutes or obscures the detection of subtle changes in gene expression in an individual cell type. However, for studies in which only the most highly differentially expressed genes are of interest, separating and analysing individual cell types may be unnecessary
Semantics for first-order affine inductive data types via slice categories
Affine type systems are substructural type systems where copying of
information is restricted, but discarding of information is permissible at all
types. Such type systems are well-suited for describing quantum programming
languages, because copying of quantum information violates the laws of quantum
mechanics. In this paper, we consider a first-order affine type system with
inductive data types and present a novel categorical semantics for it. The most
challenging aspect of this interpretation comes from the requirement to
construct appropriate discarding maps for our data types which might be defined
by mutual/nested recursion. We show how to achieve this for all types by taking
models of a first-order linear type system whose atomic types are discardable
and then presenting an additional affine interpretation of types within the
slice category of the model with the tensor unit. We present some concrete
categorical models for the language ranging from classical to quantum. Finally,
we discuss potential ways of dualising and extending our methods and using them
for interpreting coalgebraic and lazy data types
Differential calculus with imprecise input and its logical framework
We develop a domain-theoretic Differential Calculus for locally Lipschitz functions on finite dimensional real spaces with imprecise input/output. The inputs to these functions are hyper-rectangles and the outputs are compact real intervals. This extends the domain of application of Interval Analysis and exact arithmetic to the derivative. A new notion of a tie for these functions is introduced, which in one dimension represents a modification of the notion previously used in the one-dimensional framework. A Scott continuous sub-differential for these functions is then constructed, which satisfies a weaker form of calculus compared to that of the Clarke sub-gradient. We then adopt a Program Logic viewpoint using the equivalence of the category of stably locally compact spaces with that of semi-strong proximity lattices. We show that given a localic approximable mapping representing a locally Lipschitz map with imprecise input/output, a localic approximable mapping for its sub-differential can be constructed, which provides a logical formulation of the sub-differential operator
G-structures and Domain Walls in Heterotic Theories
We consider heterotic string solutions based on a warped product of a
four-dimensional domain wall and a six-dimensional internal manifold,
preserving two supercharges. The constraints on the internal manifolds with
SU(3) structure are derived. They are found to be generalized half-flat
manifolds with a particular pattern of torsion classes and they include
half-flat manifolds and Strominger's complex non-Kahler manifolds as special
cases. We also verify that previous heterotic compactifications on half-flat
mirror manifolds are based on this class of solutions.Comment: 29 pages, reference added, typos correcte
Cellular expression, trafficking, and function of two isoforms of human ULBP5/RAET1G
Background:
The activating immunoreceptor NKG2D is expressed on Natural Killer (NK) cells and subsets of T cells. NKG2D contributes to anti-tumour and anti-viral immune responses in vitro and in vivo. The ligands for NKG2D in humans are diverse proteins of the MIC and ULBP/RAET families that are upregulated on the surface of virally infected cells and tumours. Two splicing variants of ULBP5/RAET1G have been cloned previously, but not extensively characterised.
Methodology/Principal Findings:
We pursue a number of approaches to characterise the expression, trafficking, and function of the two isoforms of ULBP5/RAET1G. We show that both transcripts are frequently expressed in cell lines derived from epithelial cancers, and in primary breast cancers. The full-length transcript, RAET1G1, is predicted to encode a molecule with transmembrane and cytoplasmic domains that are unique amongst NKG2D ligands. Using specific anti-RAET1G1 antiserum to stain tissue microarrays we show that RAET1G1 expression is highly restricted in normal tissues. RAET1G1 was expressed at a low level in normal gastrointestinal epithelial cells in a similar pattern to MICA. Both RAET1G1 and MICA showed increased expression in the gut of patients with celiac disease. In contrast to healthy tissues the RAET1G1 antiserum stained a wide variety or different primary tumour sections. Both endogenously expressed and transfected RAET1G1 was mainly found inside the cell, with a minority of the protein reaching the cell surface. Conversely the truncated splicing variant of RAET1G2 was shown to encode a soluble molecule that could be secreted from cells. Secreted RAET1G2 was shown to downregulate NKG2D receptor expression on NK cells and hence may represent a novel tumour immune evasion strategy.
Conclusions/Significance:
We demonstrate that the expression patterns of ULBP5RAET1G are very similar to the well-characterised NKG2D ligand, MICA. However the two isoforms of ULBP5/RAET1G have very different cellular localisations that are likely to reflect unique functionality
Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages
This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments
Lymphocyte subsets and the role of Th1/Th2 balance in stressed chronic pain patients
Background: The complex regional pain syndrome (CRPS) and fibromyalgia (FM) are chronic pain syndromes occurring in highly stressed individuals. Despite the known connection between the nervous system and immune cells, information on distribution of lymphocyte subsets under stress and pain conditions is limited. Methods: We performed a comparative study in 15 patients with CRPS type I, 22 patients with FM and 37 age- and sex-matched healthy controls and investigated the influence of pain and stress on lymphocyte number, subpopulations and the Th1/Th2 cytokine ratio in T lymphocytes. Results: Lymphocyte numbers did not differ between groups. Quantitative analyses of lymphocyte subpopulations showed a significant reduction of cytotoxic CD8+ lymphocytes in both CRPS (p < 0.01) and FM (p < 0.05) patients as compared with healthy controls. Additionally, CRPS patients were characterized by a lower percentage of IL-2-producing T cell subpopulations reflecting a diminished Th1 response in contrast to no changes in the Th2 cytokine profile. Conclusions: Future studies are warranted to answer whether such immunological changes play a pathogenetic role in CRPS and FM or merely reflect the consequences of a pain-induced neurohumoral stress response, and whether they contribute to immunosuppression in stressed chronic pain patients. Copyright (c) 2008 S. Karger AG, Basel
Genomic analysis of human lung fibroblasts exposed to vanadium pentoxide to identify candidate genes for occupational bronchitis
BACKGROUND: Exposure to vanadium pentoxide (V(2)O(5)) is a cause of occupational bronchitis. We evaluated gene expression profiles in cultured human lung fibroblasts exposed to V(2)O(5 )in vitro in order to identify candidate genes that could play a role in inflammation, fibrosis, and repair during the pathogenesis of V(2)O(5)-induced bronchitis. METHODS: Normal human lung fibroblasts were exposed to V(2)O(5 )in a time course experiment. Gene expression was measured at various time points over a 24 hr period using the Affymetrix Human Genome U133A 2.0 Array. Selected genes that were significantly changed in the microarray experiment were validated by RT-PCR. RESULTS: V(2)O(5 )altered more than 1,400 genes, of which ~300 were induced while >1,100 genes were suppressed. Gene ontology categories (GO) categories unique to induced genes included inflammatory response and immune response, while GO catogories unique to suppressed genes included ubiquitin cycle and cell cycle. A dozen genes were validated by RT-PCR, including growth factors (HBEGF, VEGF, CTGF), chemokines (IL8, CXCL9, CXCL10), oxidative stress response genes (SOD2, PIPOX, OXR1), and DNA-binding proteins (GAS1, STAT1). CONCLUSION: Our study identified a variety of genes that could play pivotal roles in inflammation, fibrosis and repair during V(2)O(5)-induced bronchitis. The induction of genes that mediate inflammation and immune responses, as well as suppression of genes involved in growth arrest appear to be important to the lung fibrotic reaction to V(2)O(5)
Difference-based clustering of short time-course microarray data with replicates
<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p
Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation
<p>Abstract</p> <p>Background</p> <p>External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.</p> <p>Results</p> <p>We therefore develop the concept of graph-decorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways in a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the features (e.g. genes) and are thus able to define a graph-delayed correlation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph-decorrelation algorithm (GraDe). To analyze alterations in the gene response in <it>IL-6 </it>stimulated primary mouse hepatocytes, we performed a time-course microarray experiment and applied GraDe. In contrast to standard techniques, the extracted time-resolved gene expression profiles showed that <it>IL-6 </it>activates genes involved in cell cycle progression and cell division. Genes linked to metabolic and apoptotic processes are down-regulated indicating that <it>IL-6 </it>mediated priming renders hepatocytes more responsive towards cell proliferation and reduces expenditures for the energy metabolism.</p> <p>Conclusions</p> <p>GraDe provides a novel framework for the decomposition of large-scale 'omics' data. We were able to show that including prior knowledge into the separation task leads to a much more structured and detailed separation of the time-dependent responses upon <it>IL-6 </it>stimulation compared to standard methods. A Matlab implementation of the GraDe algorithm is freely available at <url>http://cmb.helmholtz-muenchen.de/grade</url>.</p
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