Biomedical subjects

Nicole A Datson

Publications and source records attributed to Nicole A Datson.

8 recordsLinked to original sources

PubMed2006

Exploring host-pathogen interactions at the epithelial surface: application of transcriptomics in lung biology.

The epithelial surface of the airways is the largest barrier-forming interface between the human body and the outside world. It is now well recognized that, at this strategic position, airway epithelial cells play an eminent role in host defense by recognizing and responding to microbial exposure. Conversely, inhaled microorganisms also respond to contact with epithelial cells. Our understanding of this cross talk is limited, requiring sophisticated experimental approaches to analyze these complex interactions. High-throughput technologies, such as DNA microarray analysis and serial analysis of gene expression (SAGE), have been developed to screen for gene expression levels at large scale within single experiments. Since their introduction, these hypothesis-generating technologies have been widely used in diverse areas such as oncology and brain research. Successful application of these genomics-based technologies has also revealed novel insights in host-pathogen interactions in both the host and pathogen. This review aims to provide an overview of the SAGE and microarray technology illustrated by their application in the analysis of host-pathogen interactions. In particular, the interactions between epithelial cells in the human lungs and clinically relevant microorganisms are the central focus of this review.

Epithelial Cells↗

PubMed2006

The effect of chronic exposure to highly aggressive mice on hippocampal gene expression of non-aggressive subordinates.

Exposure to a chronic psychosocial stressor changes the behavioral and neuroendocrine response pattern and causes structural changes in the rodent hippocampus. However, the underlying molecular mechanism of these changes induced by chronic stress is largely unknown. Recently, it was shown that exposure to a dominant highly aggressive mouse in the sensory contact model induced long-lasting stress symptoms in subordinate mice genetically selected for long attack latency (LAL mice). The aim of the present study was to study the effect of chronic stress on hippocampal gene expression in these subordinate LAL mice. GeneChips (Affymetrix) were used to compare gene expression profiles of LAL mice exposed to a sensory contact stressor for 25 days and their controls (one array per mouse, n=5 per line). After this stress paradigm, 131 genes were found differentially expressed (P<0.01). Strikingly, all of these genes showed a subtle downregulation in response to a chronic stressor. Interestingly, a significant overrepresentation of genes encoding structural components of ribosomes were found, suggesting diminished protein biosynthesis in the hippocampus of chronically stressed LAL mice. In addition, several genes of the NFkappaB signaling cascade, a pathway crucially involved in neuronal viability and neurite growth, were found to be downregulated. Together, we hypothesize that reduced NFkappaB signaling and diminished protein biosynthesis form part of the molecular mechanisms by which a chronic psychosocial stressor induces structural alterations in hippocampus of LAL mice.

Aggression↗

PubMed2006

A molecular signature of epithelial host defense: comparative gene expression analysis of cultured bronchial epithelial cells and keratinocytes.

BACKGROUND: Epithelia are barrier-forming tissues that protect the organism against external noxious stimuli. Despite the similarity in function of epithelia, only few common protective mechanisms that are employed by these tissues have been systematically studied. Comparative analysis of genome-wide expression profiles generated by means of Serial Analysis of Gene Expression (SAGE) is a powerful approach to yield further insight into epithelial host defense mechanisms. We performed an extensive comparative analysis of previously published SAGE data sets of two types of epithelial cells, namely bronchial epithelial cells and keratinocytes, in which the response to pro-inflammatory cytokines was assessed. These data sets were used to elucidate a common denominator in epithelial host defense. RESULTS: Bronchial epithelial cells and keratinocytes were found to have a high degree of overlap in gene expression. Using an in silico approach, an epithelial-specific molecular signature of gene expression was identified in bronchial epithelial cells and keratinocytes comprising of family members of keratins, small proline-rich proteins and proteinase inhibitors. Whereas some of the identified genes were known to be involved in inflammation, the majority of the signature represented genes that were previously not associated with host defense. Using polymerase chain reaction, presence of expression of selected tissue-specific genes was validated. CONCLUSION: Our comparative analysis of gene transcription reveals that bronchial epithelial cells and keratinocytes both express a subset of genes that is likely to be essential in epithelial barrier formation in these cell types. The expression of these genes is specific for bronchial epithelial cells and keratinocytes and is not seen in non-epithelial cells. We show that bronchial epithelial cells, similar to keratinocytes, express components that are able to form a cross-linked protein envelope that may contribute to an effective barrier against noxious stimuli and pathogens.

Algorithms↗

PubMed2005

Transcriptional response of bronchial epithelial cells to Pseudomonas aeruginosa: identification of early mediators of host defense.

The airway epithelium responds to microbial exposure by altering expression of a variety of genes to increase innate host defense. We aimed to delineate the early transcriptional response in human primary bronchial epithelial cells exposed for 6 h to a mixture of IL-1beta and TNF-alpha or heat-inactivated Pseudomonas aeruginosa. Because molecular mechanisms of epithelial innate host defense are not fully understood, the open-ended expression-profiling technique SAGE was applied to construct gene expression profiles covering 30,000 genes: 292 genes were found to be differentially expressed. Expression of seven genes was confirmed by real-time qPCR. Among differentially expressed genes, four classes or families were identified: keratins, proteinase inhibitors, S100 calcium-binding proteins, and IL-1 family members. Marked transcriptional changes were observed for keratins that form a key component of the cytoskeleton in epithelial cells. Expression of antimicrobial proteinase inhibitors SLPI and elafin was elevated after microbial or cytokine exposure. Interestingly, expression of numerous S100 family members was observed, and eight members, including S100A8 and S100A9, were among the most differentially expressed genes. Differential expression was also observed for the IL-1 family members IL-1beta, IL-1 receptor antagonist, and IL-1F9, a newly discovered IL-1 family member. Clustering of differentially expressed genes into biological processes revealed that the early inflammatory response in airway epithelial cells to IL-1beta-TNF-alpha and P. aeruginosa is characterized by expression of genes involved in epithelial barrier formation and host defense.

Bronchi↗

PubMed2003

GeneChip analysis of hippocampal gene expression profiles of short- and long-attack-latency mice: technical and biological implications.

To gain insight into the molecular mechanisms underlying the behavioral differences between two mouse lines genetically selected for long and short attack latency (LAL and SAL mice, respectively), we have recently applied the large-scale gene expression profiling method known as serial analysis of gene expression (SAGE) to generate hippocampal gene expression profiles of these mice. The aim of the present study is to extend and validate the SAGE expression profile of hippocampi of LAL and SAL mice using GeneChips (Affymetrix, Santa Clara, CA; one array per mouse, n = 5 per mouse line). As was the case with SAGE, GeneChips detect only medium- to high-abundance genes in the hippocampus. Extensive analysis of GeneChip data using very stringent parameters shows differential expression of 122 genes, all except one of which were expressed at higher levels in LAL mice (P < 0.01). As predicted by SAGE, our data indicate higher expression of several cytoskeleton genes in LAL mice, suggesting longer axonal and dendritic projections in the hippocampus of these mice. This is consistent with our tentative model, in which the behavioral differences between LAL and SAL mice may be related to structural differences in the hippocampus. In addition, a group of 76 genes with diverse biological function and 46 expressed sequence tags (ESTs) were all expressed at higher levels in LAL mice. A novel finding in this study was the significantly lower expression of only a single gene, growth arrest-specific gene (gas5), in LAL mice. As gas5 does not encode a protein but several small nuclear RNAs, our data suggest that small RNAs may contribute to the molecular mechanisms underlying the extreme behavioral differences between LAL and SAL mice.

Aggression↗

PubMed2003

Large-scale gene expression profiling of discrete brain regions: potential, limitations, and application in genetics of aggressive behavior.

Many behavioral geneticists are interested in unraveling the molecular mechanisms underlying aggressive behavior. So far, most scientists have based their search for aggression-related genes on a preliminary functional hypothesis. Large-scale gene expression profiling techniques, such as serial analysis of gene expression (SAGE) and DNA microarrays, now enable the screening of expression levels of thousands of genes simultaneously, allowing the identification of new candidate aggression-related genes expressed in brain and thus the generation of new hypotheses. However, expression profiling in the brain is challenging, as brain is a complex heterogeneous tissue where large numbers of genes are expressed and relatively small changes in gene expression occur. In this special issue, we focus on the principles of SAGE and DNA microarrays, as well as their advantages and disadvantages and application to analysis in brain tissue in order to identify aggression-related genes.

Aggression↗

PubMed2003

Serial analysis of gene expression predicts structural differences in hippocampus of long attack latency and short attack latency mice.

The genetically selected long attack latency (LAL) and short attack latency (SAL) mice differ in a wide variety of behavioural traits and display differences in the serotonergic system and the hypothalamus-pituitary-adrenocortical (HPA)-axis. Serial analysis of gene expression (SAGE) was used to generate a hippocampal expression profile of almost 30 000 genes in LAL and SAL mice. Using SAGE, we found differential expression of 191 genes. Among these were genes involved in growth, signal transduction, and cell metabolism. The SAGE study was supported by GeneChip analysis (Affymetrix). Strikingly, both SAGE and GeneChips showed a higher expression of numerous cytoskeleton genes, such as cofilin and several tubulin isotypes in LAL mice. LAL mice also showed a higher expression of several calmodulin-related genes and genes encoding components of a MAPK cascade, namely raf-related oncogene and ERK2. The findings were confirmed by in situ hybridization. Our results of differential expression of cytoskeleton and signal transduction genes therefore suggest differential regulation of the raf/ERK pathway that may be related to structural differences in the hippocampus of LAL and SAL mice. As stress-related disorders, such as depression, are also linked to differential regulation of the HPA-axis and the serotonergic system and are associated with altered hippocampal morphology, differential regulation of these genes may be involved in the pathogenesis of these diseases.

Aggression↗

PubMed2002

Evaluation of Affymetrix Gene Chip sensitivity in rat hippocampal tissue using SAGE analysis. Serial Analysis of Gene Expression.

DNA microarrays are a powerful tool for monitoring thousands of transcript levels simultaneously. However, the use of DNA microarrays in studying the central nervous system faces several challenges. These include the detection of low-abundance transcripts in highly complex tissue as well as estimating relatively low-magnitude changes in transcript levels in response to experimental manipulation. Many transcripts important to brain function have low expression levels or are expressed in relatively few cells, making them difficult to detect in the complex background of brain tissue. The aim of the present study is to evaluate the sensitivity of Gene Chip detection of transcripts in brain by using results from serial analysis of gene expression (SAGE) studies. The results of this comparison indicate that Affymetrix Gene Chips, like SAGE, only reliably detect medium- to high-abundance transcripts and that detection of low-abundance transcripts, many of which have great relevance to biological function in brain, is inconsistent. Specifically, we estimate that Gene Chips reliably detect no more than 30% of the hippocampal transcriptome when using a gross hippocampal dissection as the source tissue. This report provides the first broad evaluation of Affymetrix Gene Chip sensitivity relevant to studying the brain.

Animals↗