Feature extraction and signal processing for nylon DNA microarrays

BACKGROUND: High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. RESULTS: We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis). CONCLUSIONS: Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper

Altered Protein Networks and Cellular Pathways in Severe West Nile Disease in Mice

Background:The recent West Nile virus (WNV) outbreaks in developed countries, including Europe and the United States, have been associated with significantly higher neuropathology incidence and mortality rate than previously documented. The changing epidemiology, the constant risk of (re-)emergence of more virulent WNV strains, and the lack of effective human antiviral therapy or vaccines makes understanding the pathogenesis of severe disease a priority. Thus, to gain insight into the pathophysiological processes in severe WNV infection, a kinetic analysis of protein expression profiles in the brain of WNV-infected mice was conducted using samples prior to and after the onset of clinical sympt

Kinetic analysis of mouse brain proteome alterations following chikungunya virus infection before and after appearance of clinical symptoms

Recent outbreaks of Chikungunya virus (CHIKV) infection have been characterized by an increasing number of severe cases with atypical manifestations including neurological complications. In parallel, the risk map of CHIKV outbreaks has expanded because of improved vector competence. These features make CHIKV infection a major public health concern that requires a better understanding of the underlying physiopathological processes for the development of antiviral strategies to protect individuals from severe disease. To decipher the mechanisms of CHIKV in

TranscriptomeBrowser: A Powerful and Flexible Toolbox to Explore Productively the Transcriptional Landscape of the Gene Expression Omnibus Database

International audienceAs public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data.\ We used a modified version of the Markov clustering algorithm to systematically extract clusters of co-regulated genes from hundreds of microarray datasets stored in the Gene Expression Omnibus database (n = 1,484). This approach led to the definition of 18,250 transcriptional signatures (TS) that were tested for functional enrichment using the DAVID knowledgebase. Over-representation of functional terms was found in a large proportion of these TS (84%). We developed a JAVA application, TBrowser that comes with an open plug-in architecture and whose interface implements a highly sophisticated search engine supporting several Boolean operators (http://tagc.univ-mrs.fr/tbrowser/). User can search and analyze TS containing a list of identifiers (gene symbols or AffyIDs) or associated with a set of functional terms.\ As proof of principle, TBrowser was used to define breast cancer cell specific genes and to detect chromosomal abnormalities in tumors. Finally, taking advantage of our large collection of transcriptional signatures, we constructed a comprehensive map that summarizes gene-gene co-regulations observed through all the experiments performed on HGU133A Affymetrix platform. We provide evidences that this map can extend our knowledge of cellular signaling pathways

Entropy Measures Quantify Global Splicing Disorders in Cancer

Most mammalian genes are able to express several splice variants in a phenomenon known as alternative splicing. Serious alterations of alternative splicing occur in cancer tissues, leading to expression of multiple aberrant splice forms. Most studies of alternative splicing defects have focused on the identification of cancer-specific splice variants as potential therapeutic targets. Here, we examine instead the bulk of non-specific transcript isoforms and analyze their level of disorder using a measure of uncertainty called Shannon's entropy. We compare isoform expression entropy in normal and cancer tissues from the same anatomical site for different classes of transcript variations: alternative splicing, polyadenylation, and transcription initiation. Whereas alternative initiation and polyadenylation show no significant gain or loss of entropy between normal and cancer tissues, alternative splicing shows highly significant entropy gains for 13 of the 27 cancers studied. This entropy gain is characterized by a flattening in the expression profile of normal isoforms and is correlated to the level of estimated cellular proliferation in the cancer tissue. Interestingly, the genes that present the highest entropy gain are enriched in splicing factors. We provide here the first quantitative estimate of splicing disruption in cancer. The expression of normal splice variants is widely and significantly disrupted in at least half of the cancers studied. We postulate that such splicing disorders may develop in part from splicing alteration in key splice factors, which in turn significantly impact multiple target genes

Cerebrospinal fluid biomarker candidates associated with human WNV neuroinvasive disease

During the last decade, the epidemiology of WNV in humans has changed in the southern regions of Europe, with high incidence of West Nile fever (WNF) cases, but also of West Nile neuroinvasive disease (WNND). The lack of human vaccine or specific treatment against WNV infection imparts a pressing need to characterize indicators associated with neurological involvement. By its intimacy with central nervous system (CNS) structures, modifications in the cerebrospinal fluid (CSF) composition could accurately reflect CNS pathological process. Until now, few studies investigated the association between imbalance of CSF elements and severity of WNV infection. The aim of the present study was to apply the iTRAQ technology in order to identify the CSF proteins whose abundances are modified in patients with WNND. Forty-seven proteins were found modified in the CSF of WNND patients as compared to control groups, and most of them are reported for the first time in the context of WNND. On the basis of their known biological functions, several of these proteins were associated with inflammatory response. Among them, Defensin-1 alpha (DEFA1), a protein reported with anti-viral effects, presente

Gene Expression Profiles Characterize Inflammation Stages in the Acute Lung Injury in Mice

Acute Lung Injury (ALI) carries about 50 percent mortality and is frequently associated with an infection (sepsis). Life-support treatment with mechanical ventilation rescues many patients, although superimposed infection or multiple organ failure can result in death. The outcome of a patient developing sepsis depends on two factors: the infection and the pre-existing inflammation. In this study, we described each stage of the inflammation process using a transcriptional approach and an animal model. Female C57BL6/J mice received an intravenous oleic acid injection to induce an acute lung injury (ALI). Lung expression patterns were analyzed using a 9900 cDNA mouse microarray (MUSV29K). Our gene-expression analysis revealed marked changes in the immune and inflammatory response metabolic pathways, notably lipid metabolism and transcription. The early stage (1 hour–1.5 hours) is characterized by a pro-inflammatory immune response. Later (3 hours–4 hours), the immune cells migrate into inflamed tissues through interaction with vascular endothelial cells. Finally, at late stages of lung inflammation (18 hours–24 hours), metabolism is deeply disturbed. Highly expressed pro-inflammatory cytokines activate transcription of many genes and lipid metabolism. In this study, we described a global overview of critical events occurring during lung inflammation which is essential to understand infectious pathologies such as sepsis where inflammation and infection are intertwined. Based on these data, it becomes possible to isolate the impact of a pathogen at the transcriptional level from the global gene expression modifications resulting from the infection associated with the inflammation

Structure and morphology of nanometer-sized Pd clusters grown at high temperature on natural graphite single crystals

Performing both ex situ transmission electron microscopy (TEM) and in situ scanning tunnelling microscopy (STM) experiments on the same samples, we have characterized in detail a model catalyst (Pd/graphite). The Pd clusters were epitaxially grown at high temperature on clean natural graphite substrates under ultra high vacuum (UHV) conditions. For the chosen growth conditions the density of clusters is rather low (109 cm−2), and their size is typically few tens of nanometers. TEM diffraction studies reveal that most of the clusters (92% ) are in a same epitaxial orientation which is defined by: (1 1 1)Pd $\parallel$ (0 0 . 1)Gr and $[1 1\bar{2}]_{\rm Pd}$ $\parallel$ $[1 \bar{1} . 0]_{\rm Gr}$. Moreover, both STM imaging and TEM observations show that the clusters have truncated tetrahedron shapes. The combination of TEM and STM characterizations of the same samples appears to be a very efficient way to get a detailed knowledge of the global properties of a collection of supported clusters (spatial and size distributions) as well as of their individual properties (structure, morphology)