Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells

Background  

cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accurately due to "noise" from random and systematic errors. While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells.     

Gene expression databases and data mining

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.     

Predicting Novel Human Gene Ontology Annotations Using Semantic Analysis

The correct interpretation of many molecular biology experiments depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are meant to act as repositories for our biological knowledge as we acquire and refine it. Hence, by definition, they are incomplete at any given time. In this paper, we describe a technique that improves our previous method for predicting novel GO annotations by extracting implicit semantic relationships between genes and functions. In this work, we use a vector space model and a number of weighting schemes in addition to our previous latent semantic indexing approach. The technique described here is able to take into consideration the hierarchical structure of the Gene Ontology (GO) and can weight differently GO terms situated at different depths. The prediction abilities of 15 different weighting schemes are compared and evaluated. Nine such schemes were previously used in other problem domains, while six of them are introduced in this paper. The best weighting scheme was a novel scheme, n2tn. Out of the top 50 functional annotations predicted using this weighting scheme, we found support in the literature for 84 percent of them, while 6 percent of the predictions were contradicted by the existing literature. For the remaining 10 percent, we did not find any relevant publications to confirm or contradict the predictions. The n2tn weighting scheme also outperformed the simple binary scheme used in our previous approach.     

Gene expression profiling demonstrates a novel role for foetal fibrocytes and the umbilical vessels in human fetoplacental development

There is a difference in the susceptibility to inflammation between the umbilical vein (UV) and the umbilical arteries (UAs). This led us to hypothesize that there is an intrinsic difference in the pro-inflammatory response between UA and UV. Real-time quantitative RT-PCR and microarray analysis revealed higher expression of interleukin (IL)-1β and IL-8 mRNA in the UV and differential expression of 567 genes between the UA and UV associated with distinct biological processes, including the immune response. Differential expression of human leukocyte antigen (HLA)-DRA mRNA between the UA and UV was due to unexpected HLA-DR⁺ cells migrating via the umbilical vessels into Wharton's jelly, more frequently in the UV. A significant proportion of these cells co-expressed CD45 and type I pro-collagen, and acquired CD163 or α-smooth muscle actin immunoreactivity in Wharton's jelly. Migrating cells were also found in the chorionic and stem villous vessels. Furthermore, the extent of migration increased with progression of gestation, but diminished in intrauterine growth restriction (IUGR). The observations herein strongly suggest that circulating foetal fibrocytes, routing via umbilical and placental vessels, are a reservoir for key cellular subsets in the placenta. This study reports fibrocytes in the human umbilical cord and placenta for the first time, and a novel role for both circulating foetal cells and the umbilical vessels in placental development, which is deranged in IUGR.     

KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours

MOTIVATION: The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments. RESULTS: We developed KUTE (Karmanos Universal daTabase for microarray Experiments), as a plug-in for BASE 2.0 that addresses these issues. KUTE provides an automatic experiment annotation feature and a completely redesigned data work-flow that dramatically reduce the human-computer interaction time. For instance, in BASE 2.0 a typical Affymetrix experiment involving 100 arrays required 4 h 30 min of user interaction time forexperiment annotation, and 45 min for data upload/download. In contrast, for the same experiment, KUTE required only 28 min of user interaction time for experiment annotation, and 3.3 min for data upload/download. AVAILABILITY: http://vortex.cs.wayne.edu/kute/index.html.     

Development of Central Nervous System Autoimmunity Is Impaired in the Absence of Wiskott-Aldrich Syndrome Protein

Wiskott-Aldrich Syndrome protein (WASP) is a key regulator of the actin cytoskeleton in hematopoietic cells. Defective expression of WASP leads to multiple abnormalities in different hematopoietic cells. Despite severe impairment of T cell function, WAS patients exhibit a high prevalence of autoimmune disorders. We attempted to induce EAE, an animal model of organ-specific autoimmunity affecting the CNS that mimics human MS, in Was^−/− mice. We describe here that Was^−/− mice are markedly resistant against EAE, showing lower incidence and milder score, reduced CNS inflammation and demyelination as compared to WT mice. Microglia was only poorly activated in Was^−/− mice. Antigen-induced T-cell proliferation, Th-1 and -17 cytokine production and integrin-dependent adhesion were increased in Was^−/− mice. However, adoptive transfer of MOG-activated T cells from Was^−/− mice in WT mice failed to induce EAE. Was^−/− mice were resistant against EAE also when induced by adoptive transfer of MOG-activated T cells from WT mice. Was^+/− heterozygous mice developed an intermediate clinical phenotype between WT and Was^−/− mice, and they displayed a mixed population of WASP-positive and -negative T cells in the periphery but not in their CNS parenchyma, where the large majority of inflammatory cells expressed WASP. In conclusion, in absence of WASP, T-cell responses against a CNS autoantigen are increased, but the ability of autoreactive T cells to induce CNS autoimmunity is impaired, most probably because of an inefficient T-cell transmigration into the CNS and defective CNS resident microglial function.     

Global functional profiling of gene expression

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independent of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function, and chromosome location. Statistical significance values are calculated for each category. We demonstrate the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer datasets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms.