Functional pathways that showed statistically significant differential expression between RV-A16 and Vehicle groups (p<0.05).

<p>Outliner is shown individually with a solid circle.</p

MUC5AC expression is upregulated in response to HRV infection.

<p>A) Immunofluorescence of MUC5AC in ALI cultures from donors 21 (non-asthma, non-smoker), 23 (non-asthma, smoker), 26 (asthma, non-smoker) and 11(asthma, smoker) show an increase in staining with HRV treatment, with only donor 23 having high baseline expression. Green: MUC5AC, blue: DAPI staining for nuclei, representative images, scale bar: 50 μm. N = 6 ALI cultures per group (asthma and non-asthma). B and C) Quantification of immunofluorescence staining presented as either dot plot (B) or box plot (C). Positively stained area was measured and presented as % of total epithelial area. Red dots indicate outliers (> 1.5x inter-quartile distance). B) Inclusion of all data from 6 non-asthmatic and 6 asthmatic donors in analysis. C) Removal of non-diseased smokers (donors 11 and 23) from the data set results in significant differences between HRV and vehicle treated tissues in both non-asthmatic and asthmatic donors as determined by ANOVA and Tukey HSD test.</p

Distributions of differentially expressed genes in asthmatic samples after treatment of vehicle or RV-A16.

<p>579 genes in the “Asthma vs. non-asthma at baseline” group had baseline difference between asthmatic and non-asthmatic cells (p<0.05); 497 genes in the “Asthma vs. non-asthma after HRV infection” group had asthma-related viral response (p<0.05); and 1485 genes in the “HRV response group had strong expression changes associated with viral infection across both asthma and non-asthma donors. The numbers of genes only in one group or common for either two or three groups are shown by either exclusive or overlapping areas in Venn diagrams. The diagrams were generated with an online tool available at <a href="http://bioinfogp.cnb.csic.es/tools/venny/" target="_blank">http://bioinfogp.cnb.csic.es/tools/venny/</a>.</p

Donor information.

<p>Donor information.</p

A human tissue-based functional assay platform to evaluate the immune function impact of small molecule inhibitors that target the immune system

<div><p>While the immune system is essential for the maintenance of the homeostasis, health and survival of humans, aberrant immune responses can lead to chronic inflammatory and autoimmune disorders. Pharmacological modulation of drug targets in the immune system to ameliorate disease also carry a risk of immunosuppression that could lead to adverse outcomes. Therefore, it is important to understand the ‘immune fingerprint’ of novel therapeutics as they relate to current and, clinically used immunological therapies to better understand their potential therapeutic benefit as well as immunosuppressive ability that might lead to adverse events such as infection risks and cancer. Since the mechanistic investigation of pharmacological modulators in a drug discovery setting is largely compound- and mechanism-centric but not comprehensive in terms of immune system impact, we developed a human tissue based functional assay platform to evaluate the impact of pharmacological modulators on a range of innate and adaptive immune functions. Here, we demonstrate that it is possible to generate a qualitative and quantitative immune system impact of pharmacological modulators, which might help better understand and predict the benefit-risk profiles of these compounds in the treatment of immune disorders.</p></div

ALI cultured HAECs were infectible by RV-A16.

<p>Immunofluorescence micrographs of transverse sections of ALI cultures shows RV-A16 replicated in ALI cultured HAECs. Positive immunofluorescence staining for mabj2 (in green) was not observed in uninfected control tissues (top panel), but was observed in RV-A16 infected tissues (bottom panel); DAPI staining in blue shows cell nuclei in the tissues. Scale bars: 50 μm.</p

Expression of secreted cytokines/chemokines in culture medium.

<p>16/42 cytokines tested had robust expression levels and were significantly up-regulated at 24 hr after RV-A16 infection across 12 donors (p value<0.05). Differences were not significant between asthma and non-asthma groups (p>0.05). Red lines represent asthma samples, blue lines represent non-asthma samples. Each line represents the mean and standard deviation of log2 concentration of each cytokine/chemokine.</p

Immune function impact profiles of small molecule inhibitors.

<p>Small molecule inhibitors were evaluated in six different functional assays with nine different read-outs. For a given compound on the Y-axis, each symbol on the X-axis represents the protein binding corrected cellular potency of that compound in the corresponding assay. The potencies of the evaluated compounds in these assays are displayed as IC₅₀ values in the X-axis. The reported IC₅₀ values were generated from a composite of 8–10 point dose response curves from n = 6–8 donors for each compound in each assay. Immune function impact of a broader set (A) or a subset (B) of inhibitors are presented.</p

Assays to evaluate immune function impact of small molecule inhibitors.

<p>All the assays were established using healthy donor peripheral blood mononuclear cells (PBMCs) or whole blood. The immune functions evaluated, the tissues analyzed, stimulations used as well as the tissue analysis methods are listed for each assay. Small molecule inhibitors that are known to inhibit these functions were used as positive controls (assay controls) in each run of the assay, to ensure consistent technical performance and data robustness.</p

Impact of small molecule inhibitors on gene expression profiles in the T cell stimulation assay.

<p>(A) A nanostring gene expression panel was used to evaluate mRNA profiles of PBMCs 24 h following treatment with 1μM of the SM inhibitors in the T cell stimulation assay. The gene expression profiles of unstimulated and compound treated stimulated samples are shown. All data were normalized to housekeeping genes and stimulated DMSO control samples. Hierarchical agglomerative clustering of genes with greater than a 2-fold change (p-value<0.05) is shown. (B) Transcript expression of IL-2 under unstimulated, stimulated, and compound treated conditions. The mRNA expression levels of the cytokine genes IFNγ (C), IL4 (D), IL13 (E), IL17F (F) as well as the transcription factors Tbx21 (G), GATA3 (H), RORc (I) and Foxp3 (J) are depicted as examples from the gene expression dataset. The gene expression profiles in (A) is a composite of PBMCs from n = 3 donors, while the individual gene expression profiles in (B-J) are mean±SEM of mRNA expression from n = 3 PBMC donors.</p