A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies.
Examining smoking-induced differential gene expression changes in buccal mucosa.
Specimen part
View SamplesAs part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we present results of our DNA microarray analysis of samples from a timecourse study of individuals given ethanol orally, and then evaluated by breathalyzer to monitor blood alcohol content (BAC). At five blood alcohol levels, T1-T5, blood was drawn such that the samples represented 0%, 0.04%, 0.08% BAC, and return to 0.04%, and 0.02% BAC. Microarray analysis showed that changes in gene expression could be detected across the time-course. We verified these expression changes by quantitative polymerase chain reaction (qPCR). Candidate target genes identified from the microarray analysis were clustered by expression change pattern, examined for shared functions and functional network membership. Five coordinately expressed groups were revealed and functional analysis showed shared transcription factor binding sites and functions for members of the clusters. These functions include protein synthesis and modification, expected for changes in gene expression, hematological and immune functions, expected for a blood sample, and pancreatic and hepatic function, expected as response to ethanol. The results provide a first look at changing gene expression patterns in blood during acute increase of ethanol concentration and its depletion due to metabolism or excretion and demonstrate that it is possible to detect significant changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study can be utilized as part of a workflow to identify target genes by timecourse changes in gene expression that may affect pilot performance.
Microarray characterization of gene expression changes in blood during acute ethanol exposure.
Sex, Specimen part
View SamplesBackground. Infections caused by Staphylococcus aureus are associated with significant morbidity and mortality and are an increasing threat not only in hospital settings. The expression of the staphylococcal virulence factor repertoire is known to be affected by the alternative sigma factor B (SigB). However, its impact during infection still is a matter of debate. Methods. Kidney tissue of controls or mice infected with S. aureus HG001 or its isogenic sigB mutant was analyzed by transcriptome profiling to monitor the host response, and additionally expression of selected S. aureus genes was monitored by RT-qPCR. Results. Direct transcript analysis by RT-qPCR revealed significant SigB activity in all mice infected with the wild type strain (WT), but not in its isogenic sigB mutant (p<0.0001). Despite a clear cut difference in the SigB-dependent transcription pattern of virulence genes (clfA, aur, and hla), the host reaction to infection (either WT or sigB mutant) was almost identical. Conclusions. Despite its significant activity in vivo, loss of SigB did not have an effect on the outcome of infection as well as on murine kidney gene expression pattern. Thus, these data support the role of SigB as virulence modulator rather than being a virulence determinant by itself.
The alternative sigma factor B modulates virulence gene expression in a murine Staphylococcus aureus infection model but does not influence kidney gene expression pattern of the host.
Sex, Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Subject, Time
View SamplesHealthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Subject, Time
View SamplesHealthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Subject, Time
View SamplesHealthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.
Subject, Time
View SamplesThe respiratory system is a complex network of many cell types, including subsets of macrophages and dendritic cels, that work together to maintain steady-state respiration. Due to limitations in acquiring cells from healthy human lung, these subsets remain poorly characterized transcriptionally and phenotypically. We set out to systemically identify these subsets in human airways, by developing a schema of isolating large numbers of cells by whole lung bronchoalveolar lavage. Six subsets of phagocytic antigen presenting cells were consistently observed, which varied in their ability to internalize bacterial particles. Subsets could be further separated by their inherent capacities to upregulate CD83, CD86, and CCR7. Whole genome transcriptional profiling revealed a clade of true dendritic cells distinct from a macrophage/monocyte clade. Each clade, and each member of both clades, could be discerned by specific genes of increased expression, which would serve as markers for future studies in healthy and diseased states.
Transcriptional Classification and Functional Characterization of Human Airway Macrophage and Dendritic Cell Subsets.
Sex, Age
View Samplesdrl expression initiates during gastrulation and condenses as a band of cells at the prospective lateral embryo margin. In late epiboly, drl:EGFP is detectable as a band of scattered EGFP-fluorescent cells; after gastrulation, drl:EGFP-positive cells coalesce at the embryo margin that then in somitogenesis break down into the anterior and posterior lateral plate with subsequent cell migrations that form the posterior vascular/hematopoietic stripes and the anterior cardiovascular and myeloid precursors.
Chamber identity programs drive early functional partitioning of the heart.
Age, Specimen part
View SamplesWe report the application of ultrashort metabolic labeling of RNA for high-throughput profiling of RNA processing in Drosophila S2 cells. Overall design: Examination of 3 different labeling timepoints in Drosophila S2 cells.
The kinetics of pre-mRNA splicing in the <i>Drosophila</i> genome and the influence of gene architecture.
Cell line, Subject
View Samples