Integrated mRNA-miRNA analysis of visceral fat tissue transcriptome during SF.

<p>Heatmaps depict gene expression profiles of enriched pathways and differentially expressed miRNAs in response to SF. The miRNAs are linked to their respective modules based on whether these pathways harbor target genes. Note that one mRNA microarray experiment was excluded due to poor hybridization (gray column).</p

Acute sleep fragmentation causes dysregulation in glucose homeostasis as demonstrated by the development of insulin resistance in SF mice using the homeostatic model assessment (HOMA-IR).

<p>Data are presented as mean ± SEM.</p

Outline of a general approach for integrating mRNA-miRNA data.

<p>Concurrent miRNA and mRNA profiling of the same tissue under control and exposure conditions is performed. The mRNA information is processed using gene set enrichment analysis with further refinements based on leading edges of enriched biologic modules. Meanwhile, differentially expressed miRNAs as well as their computationally-derived targets are also identified. These data are then merged based on anti-correlated expression of leading edge genes and their corresponding putative miRNAs.</p

A Venn diagram summarizing overlaps among differentially expressed genes across multiple conditions and measurements: (i) flagellin-induced genes in AECs cultured in ALI as measured by RNA-seq (ALI_RNAseq); (ii) flagellin-induced genes in AECs cultured in ALI measured by microarrays (ALI_array); (iii) flagellin-induced genes in AECs cultured in monolayer as measured by RNA-seq (Monolayer_RNAseq); (iv) flagellin-induced genes in AECs cultured in monolayer as measured by microarrays (Monolayer_array).

<p>Note the widespread transcriptional response of AECs to flagellin in monolayer cultures compared to cells grown in ALI. For a given exposure condition, RNA-seq identified a much larger set of differentially expressed genes compared to microarrays. Venn diagram was generated using online tool Venny (http://bioinfogp.cnb.csic.es/tools/venny).</p

Heatmap depiction of differentially expressed genes as determined via RNA-seq and microarrays under multiple experimental conditions: (A) unstimulated AECs cultured in monolayer vs. ALI; (B) unstimulated vs. flagellin-exposed AECs cultured in monolayer; (C) unstimulated vs. flagellin-exposed AECs cultured in ALI.

<p>Note the very large number of differentially expressed genes between ALI vs. monolayer AEC cultures at baseline. When stimulated with flagellin, AECs grown in ALI displayed a blunted transcriptional response when compared to the robust response of epithelial cells cultured in monolayer. In each condition, RNA-seq identified many more differentially expressed genes compared to microarrays while capturing the majority of genes deemed significant by microarrays. Heatmaps are based on adjusted <i>P</i>-values of differentially expressed genes, and for purposes of clarity, are not drawn to the same scale in height across conditions.</p

Chronic sleep fragmentation is associated with elevated circulating triglycerides.

<p>Mice were subjected to 3 weeks of SF (n = 5) or used as controls (n = 5). Fasting plasma triglyceride levels were measured and are presented as mean ± SEM.</p

Plasticity of Airway Epithelial Cell Transcriptome in Response to Flagellin

<div><p>Airway epithelial cells (AEC) are critical components of the inflammatory and immune response during exposure to pathogens. AECs in monolayer culture and differentiated epithelial cells in air-liquid interface (ALI) represent two distinct and commonly used <i>in vitro</i> models, yet differences in their response to pathogens have not been investigated. In this study, we compared the transcriptional effects of flagellin on AECs in monolayer culture versus ALI culture using whole-genome microarrays and RNA sequencing. We exposed monolayer and ALI AEC cultures to flagellin <i>in vitro</i> and analyzed the transcriptional response by microarray and RNA-sequencing. ELISA and RT-PCR were used to validate changes in select candidates. We found that AECs cultured in monolayer and ALI have strikingly different transcriptional states at baseline. When challenged with flagellin, monolayer AEC cultures greatly increased transcription of numerous genes mapping to wounding response, immunity and inflammatory response. In contrast, AECs in ALI culture had an unexpectedly muted response to flagellin, both in number of genes expressed and relative enrichment of inflammatory and immune pathways. We conclude that <i>in vitro</i> culturing methods have a dramatic effect on the transcriptional profile of AECs at baseline and after stimulation with flagellin. These differences suggest that epithelial responses to pathogen challenges are distinctly different in culture models of intact and injured epithelium.</p></div

Validation of differential protein expression for up-regulated candidate genes.

<p>We used ELISA to assess secreted protein levels of (A) CCL20 and (B) IL8 at baseline and following stimulation with flagellin. CCL20 and IL8 was selected because they were transcriptionally up-regulated in both ALI and monolayer AEC cultures in response to flagellin. For each condition, mean value ± standard deviation is shown. One-way ANOVA <i>P</i>-values across conditions: <i>P</i> < 0.005 for CCL20 and <i>P</i> < 0.0001 for IL8.</p

Reduced glucose tolerance in mice exposed to SF compared to control animals.

<p>Mice (n = 8 control, n = 7 SF) were injected with of D-glucose (2 g/kg) intra-peritoneally and glucose levels measured at 0, 15, 30, 60 and 120 min following injection. <i>P</i>-value was based on two-way ANOVA and corresponds to the significance of exposure (glucose) effect. All data are shown as mean ± SEM.</p

Correspondence analysis of AEC transcriptome.

<p>In this analysis, the contributions of: (i) culture methodology (monolayer, ALI); (ii) whole-genome transcription profiling platform (RNA-seq, microarray); and (iii) stimulation with flagellin on gene expression variability are shown. The three depicted axes capture more than 95% of the total transcriptional variability and the distance among samples reflects differences in gene expression. Note the large distance between monolayer vs. ALI cultured AECs as assessed by RNA-seq, implying that these samples account for a significant proportion of total gene expression variability. In contrast, exposure to flagellin (as assessed by RNA-seq or microarray) has a much more modest contribution.</p