Examining smoking-induced differential gene expression changes in buccal mucosa

<p>Abstract</p> <p>Background</p> <p>Gene expression changes resulting from conditions such as disease, environmental stimuli, and drug use, can be monitored in the blood. However, a less invasive method of sample collection is of interest because of the discomfort and specialized personnel necessary for blood sampling especially if multiple samples are being collected. Buccal mucosa cells are easily collected and may be an alternative sample material for biomarker testing. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy as an RNA source for expression analysis. The current study was undertaken to determine if total RNA isolated from buccal mucosa could be used as an alternative tissue source to assay relative gene expression.</p> <p>Methods</p> <p>Total RNA was isolated from swabs, reverse transcribed and amplified. The amplified cDNA was used in RT-qPCR and microarray analyses to evaluate gene expression in buccal cells. Initially, RT-qPCR was used to assess relative transcript levels of four genes from whole blood and buccal cells collected from the same seven individuals, concurrently. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between a group of female smokers and nonsmokers.</p> <p>Results</p> <p>An amplification protocol allowed use of less buccal cell total RNA (50 ng) than had been reported previously with human microarrays. Total RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. We report here the finding of a small number of statistically significant differentially expressed genes between smokers and nonsmokers, using buccal cells as starting material. Gene Set Enrichment Analysis confirmed that these genes had a similar expression pattern to results from another study.</p> <p>Conclusions</p> <p>Our results suggest that despite a high degree of degradation, RNA from 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.</p

The genome of the versatile nitrogen fixer Azorhizobium caulinodans ORS571

<p>Abstract</p> <p>Background</p> <p>Biological nitrogen fixation is a prokaryotic process that plays an essential role in the global nitrogen cycle. <it>Azorhizobium caulinodans </it>ORS571 has the dual capacity to fix nitrogen both as free-living organism and in a symbiotic interaction with <it>Sesbania rostrata</it>. The host is a fast-growing, submergence-tolerant tropical legume on which <it>A. caulinodans </it>can efficiently induce nodule formation on the root system and on adventitious rootlets located on the stem.</p> <p>Results</p> <p>The 5.37-Mb genome consists of a single circular chromosome with an overall average GC of 67% and numerous islands with varying GC contents. Most nodulation functions as well as a putative type-IV secretion system are found in a distinct symbiosis region. The genome contains a plethora of regulatory and transporter genes and many functions possibly involved in contacting a host. It potentially encodes 4717 proteins of which 96.3% have homologs and 3.7% are unique for <it>A. caulinodans</it>. Phylogenetic analyses show that the diazotroph <it>Xanthobacter autotrophicus </it>is the closest relative among the sequenced genomes, but the synteny between both genomes is very poor.</p> <p>Conclusion</p> <p>The genome analysis reveals that <it>A. caulinodans </it>is a diazotroph that acquired the capacity to nodulate most probably through horizontal gene transfer of a complex symbiosis island. The genome contains numerous genes that reflect a strong adaptive and metabolic potential. These combined features and the availability of the annotated genome make <it>A. caulinodans </it>an attractive organism to explore symbiotic biological nitrogen fixation beyond leguminous plants.</p

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation

Abstract Background Although sleep deprivation is associated with neurobehavioral impairment that may underlie significant risks to performance and safety, there is no reliable biomarker test to detect dangerous levels of impairment from sleep loss in humans. This study employs microarrays and bioinformatics analyses to explore candidate gene expression biomarkers associated with total sleep deprivation (TSD), and more specifically, the phenotype of neurobehavioral impairment from TSD. Healthy adult volunteers were recruited to a sleep laboratory for seven consecutive days (six nights). After two Baseline nights of 10 h time in bed, 11 subjects underwent an Experimental phase of 62 h of continuous wakefulness, followed by two Recovery nights of 10 h time in bed. Another six subjects underwent a well-rested Control condition of 10 h time in bed for all six nights. Blood was drawn for measuring gene expression on days two, four, and six at 4 h intervals from 08:00 to 20:00 h, corresponding to 12 timepoints across one Baseline, one Experimental, and one Recovery day. Results Altogether 212 genes changed expression in response to the TSD Treatment, with most genes exhibiting down-regulation during TSD. Also, 28 genes were associated with neurobehavioral impairment as measured by the Psychomotor Vigilance Test. The results support previous findings associating TSD with the immune response and ion signaling, and reveal novel candidate biomarkers such as the Speedy/RINGO family of cell cycle regulators. Conclusions This study serves as an important step toward understanding gene expression changes during sleep deprivation. In addition to exploring potential biomarkers for TSD, this report presents novel candidate biomarkers associated with lapses of attention during TSD. Although further work is required for biomarker validation, analysis of these genes may aid fundamental understanding of the impact of TSD on neurobehavioral performance