Smoking-mediated up-regulation of GAD67 expression in the human airway epithelium

<p>Abstract</p> <p>Background</p> <p>The production of gamma-amino butyric acid (GABA) is dependent on glutamate decarboxylases (GAD65 and GAD67), the enzymes that catalyze the decarboxylation of glutamate to GABA. Based on studies suggesting a role of the airway epithelial GABAergic system in asthma-related mucus overproduction, we hypothesized that cigarette smoking, another disorder associated with increased mucus production, may modulate GABAergic system-related gene expression levels in the airway epithelium.</p> <p>Methods</p> <p>We assessed expression of the GABAergic system in human airway epithelium obtained using bronchoscopy to sample the epithelium and microarrays to evaluate gene expression. RT-PCR was used to confirm gene expression of GABAergic system gene in large and small airway epithelium from heathy nonsmokers and healthy smokers. The differences in the GABAergic system gene was further confirmed by TaqMan, immunohistochemistry and Western analysis.</p> <p>Results</p> <p>The data demonstrate there is a complete GABAergic system expressed in the large and small human airway epithelium, including glutamate decarboxylase, GABA receptors, transporters and catabolism enzymes. Interestingly, of the entire GABAergic system, smoking modified only the expression of GAD67, with marked up-regulation of GAD67 gene expression in both large (4.1-fold increase, p < 0.01) and small airway epithelium of healthy smokers (6.3-fold increase, p < 0.01). At the protein level, Western analysis confirmed the increased expression of GAD67 in airway epithelium of healthy smokers compared to healthy nonsmokers (p < 0.05). There was a significant positive correlation between GAD67 and MUC5AC gene expression in both large and small airway epithelium (p < 0.01), implying a link between GAD67 and mucin overproduction in association with smoking.</p> <p>Conclusions</p> <p>In the context that GAD67 is the rate limiting enzyme in GABA synthesis, the correlation of GAD67 gene expression with MUC5AC expressions suggests that the up-regulation of airway epithelium expression of GAD67 may contribute to the increase in mucus production observed in association with cigarette smoking.</p> <p>Trial registration</p> <p>NCT00224198; NCT00224185</p

The Human Airway Epithelial Basal Cell Transcriptome

The human airway epithelium consists of 4 major cell types: ciliated, secretory, columnar and basal cells. During natural turnover and in response to injury, the airway basal cells function as stem/progenitor cells for the other airway cell types. The objective of this study is to better understand human airway epithelial basal cell biology by defining the gene expression signature of this cell population.. The basal cell signature displayed overlap with genes expressed in basal-like cells from other human tissues and with that of murine airway basal cells. Consistent with self-modulation as well as signaling to other airway cell types, the human airway basal cell signature was characterized by genes encoding extracellular matrix components, growth factors and growth factor receptors, including genes related to the EGF and VEGF pathways. Interestingly, while the basal cell signature overlaps that of basal-like cells of other organs, the human airway basal cell signature has features not previously associated with this cell type, including a unique pattern of genes encoding extracellular matrix components, G protein-coupled receptors, neuroactive ligands and receptors, and ion channels.The human airway epithelial basal cell signature identified in the present study provides novel insights into the molecular phenotype and biology of the stem/progenitor cells of the human airway epithelium

Quality control in microarray assessment of gene expression in human airway epithelium

<p>Abstract</p> <p>Background</p> <p>Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3) the multi-chip normalization scaling factor ≤ 10.0.</p> <p>Results</p> <p>Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria.</p> <p>Conclusion</p> <p>Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.</p

RNA-Seq quantification of the human small airway epithelium transcriptome

<p>Abstract</p> <p>Background</p> <p>The small airway epithelium (SAE), the cell population that covers the human airway surface from the 6^thgeneration of airway branching to the alveoli, is the major site of lung disease caused by smoking. The focus of this study is to provide quantitative assessment of the SAE transcriptome in the resting state and in response to chronic cigarette smoking using massive parallel mRNA sequencing (RNA-Seq).</p> <p>Results</p> <p>The data demonstrate that 48% of SAE expressed genes are ubiquitous, shared with many tissues, with 52% enriched in this cell population. The most highly expressed gene, SCGB1A1, is characteristic of Clara cells, the cell type unique to the human SAE. Among other genes expressed by the SAE are those related to Clara cell differentiation, secretory mucosal defense, and mucociliary differentiation. The high sensitivity of RNA-Seq permitted quantification of gene expression related to infrequent cell populations such as neuroendocrine cells and epithelial stem/progenitor cells. Quantification of the absolute smoking-induced changes in SAE gene expression revealed that, compared to ubiquitous genes, more SAE-enriched genes responded to smoking with up-regulation, and those with the highest basal expression levels showed most dramatic changes. Smoking had no effect on SAE gene splicing, but was associated with a shift in molecular pattern from Clara cell-associated towards the mucus-secreting cell differentiation pathway with multiple features of cancer-associated molecular phenotype.</p> <p>Conclusions</p> <p>These observations provide insights into the unique biology of human SAE by providing quantit-ative assessment of the global transcriptome under physiological conditions and in response to the stress of chronic cigarette smoking.</p

Evaluation of the impact of a school gardening intervention on children's fruit and vegetable intake: a randomised controlled trial.

Background: Current academic literature suggests that school gardening programmes can provide an interactive environment with the potential to change children’s fruit and vegetable intake. This is the first cluster randomised controlled trial (RCT) designed to evaluate whether a school gardening programme can have an effect on children’s fruit and vegetable intake. Methods: The trial included children from 23 schools; these schools were randomised into two groups, one to receive the Royal Horticultural Society (RHS)-led intervention and the other to receive the less involved Teacher-led intervention. A 24-hour food diary (CADET) was used to collect baseline and follow-up dietary intake 18 months apart. Questionnaires were also administered to evaluate the intervention implementation. Results: A total of 641 children completed the trial with a mean age of 8.1 years (95% CI: 8.0, 8.4). The unadjusted results from multilevel regression analysis revealed that for combined daily fruit and vegetable intake the Teacher-led group had a higher daily mean change of 8 g (95% CI: −19, 36) compared to the RHS-led group -32 g (95% CI: −60, −3). However, after adjusting for possible confounders this difference was not significant (intervention effect: −40 g, 95% CI: −88, 1; p = 0.06). The adjusted analysis of process measures identified that if schools improved their gardening score by 3 levels (a measure of school gardening involvement - the scale has 6 levels from 0 ‘no garden’ to 5 ‘community involvement’), irrespective of group allocation, children had, on average, a daily increase of 81 g of fruit and vegetable intake (95% CI: 0, 163; p = 0.05) compared to schools that had no change in gardening score. Conclusions: This study is the first cluster randomised controlled trial designed to evaluate a school gardening intervention. The results have found very little evidence to support the claims that school gardening alone can improve children’s daily fruit and vegetable intake. However, when a gardening intervention is implemented at a high level within the school it may improve children’s daily fruit and vegetable intake by a portion. Improving children’s fruit and vegetable intake remains a challenging task

Gene content evolution in the arthropods

Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity