IL-33 Expression Is Lower in Current Smokers at both Transcriptomic and Protein Levels.

Rationale: IL-33 is a proinflammatory cytokine thought to play a role in the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD). A recent clinical trial using an anti-IL-33 antibody showed a reduction in exacerbation and improved lung function in ex-smokers but not current smokers with COPD. Objectives: This study aimed to understand the effects of smoking status on IL-33. Methods: We investigated the association of smoking status with the level of gene expression of IL-33 in the airways in eight independent transcriptomic studies of lung airways. Additionally, we performed Western blot analysis and immunohistochemistry for IL-33 in lung tissue to assess protein levels. Measurements and Main Results: Across the bulk RNA-sequencing datasets, IL-33 gene expression and its signaling pathway were significantly lower in current versus former or never-smokers and increased upon smoking cessation (P < 0.05). Single-cell sequencing showed that IL-33 is predominantly expressed in resting basal epithelial cells and decreases during the differentiation process triggered by smoke exposure. We also found a higher transitioning of this cellular subpopulation into a more differentiated cell type during chronic smoking, potentially driving the reduction of IL-33. Protein analysis demonstrated lower IL-33 levels in lung tissue from current versus former smokers with COPD and a lower proportion of IL-33-positive basal cells in current versus ex-smoking controls. Conclusions: We provide strong evidence that cigarette smoke leads to an overall reduction in IL-33 expression in transcriptomic and protein level, and this may be due to the decrease in resting basal cells. Together, these findings may explain the clinical observation that a recent antibody-based anti-IL-33 treatment is more effective in former than current smokers with COPD.

A Phenotypic Screen Identifies Calcium Overload as a Key Mechanism of ß-Cell Glucolipotoxicity.

Type 2 diabetes (T2D) is caused by loss of pancreatic ß-cell mass and failure of the remaining ß-cells to deliver sufficient insulin to meet demand. ß-Cell glucolipotoxicity (GLT), which refers to combined, deleterious effects of elevated glucose and fatty acid levels on ß-cell function and survival, contributes to T2D-associated ß-cell failure. Drugs and mechanisms that protect ß-cells from GLT stress could potentially improve metabolic control in patients with T2D. In a phenotypic screen seeking low-molecular-weight compounds that protected ß-cells from GLT, we identified compound A that selectively blocked GLT-induced apoptosis in rat insulinoma cells. Compound A and its optimized analogs also improved viability and function in primary rat and human islets under GLT. We discovered that compound A analogs decreased GLT-induced cytosolic calcium influx in islet cells, and all measured ß-cell-protective effects correlated with this activity. Further studies revealed that the active compound from this series largely reversed GLT-induced global transcriptional changes. Our results suggest that taming cytosolic calcium overload in pancreatic islets can improve ß-cell survival and function under GLT stress and thus could be an effective strategy for T2D treatment.

Systems biology and in vitro validation identifies family with sequence similarity 129 member A (FAM129A) as an asthma steroid response modulator.

BACKGROUND: Variation in response to the most commonly used class of asthma controller medication, inhaled corticosteroids, presents a serious challenge in asthma management, particularly for steroid-resistant patients with little or no response to treatment. OBJECTIVE: We applied a systems biology approach to primary clinical and genomic data to identify and validate genes that modulate steroid response in asthmatic children. METHODS: We selected 104 inhaled corticosteroid-treated asthmatic non-Hispanic white children and determined a steroid responsiveness endophenotype (SRE) using observations of 6 clinical measures over 4 years. We modeled each subject's cellular steroid response using data from a previously published study of immortalized lymphoblastoid cell lines under dexamethasone (DEX) and sham treatment. We integrated SRE with immortalized lymphoblastoid cell line DEX responses and genotypes to build a genome-scale network using the Reverse Engineering, Forward Simulation modeling framework, identifying 7 genes modulating SRE. RESULTS: Three of these genes were functionally validated by using a stable nuclear factor κ-light-chain-enhancer of activated B cells luciferase reporter in A549 human lung epithelial cells, IL-1ß cytokine stimulation, and DEX treatment. By using small interfering RNA transfection, knockdown of family with sequence similarity 129 member A (FAM129A) produced a reduction in steroid treatment response (P < .001). CONCLUSION: With this systems-based approach, we have shown that FAM129A is associated with variation in clinical asthma steroid responsiveness and that FAM129A modulates steroid responsiveness in lung epithelial cells.

Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells.

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR.

RGS3 controls T lymphocyte migration in a model of Th2-mediated airway inflammation.

T cell migration toward sites of antigen exposure is mediated by G protein signaling and is a key function in the development of immune responses. Regulators of G protein signaling (RGS) proteins modulate G protein signaling; however, their role in the regulation of adaptive immune responses has not been thoroughly explored. Herein we demonstrated abundant expression of the Gi/Gq-specific RGS3 in activated T cells, and that diminished RGS3 expression in a T cell thymoma increased cytokine-induced migration. To examine the role of endogenous RGS3 in vivo, mice deficient in the RGS domain (RGS3(ΔRGS)) were generated and tested in an experimental model of asthma. Compared with littermate controls, the inflammation in the RGS3(ΔRGS) mice was characterized by increased T cell numbers and the striking development of perivascular lymphoid structures. Surprisingly, while innate inflammatory cells were also increased in the lungs of RGS3(ΔRGS) mice, eosinophil numbers and Th2 cytokine production were equivalent to control mice. In contrast, T cell numbers in the draining lymph nodes (dLN) were reduced in the RGS3(ΔRGS), demonstrating a redistribution of T cells from the dLN to the lungs via increased RGS3(ΔRGS) T cell migration. Together these novel findings show a nonredundant role for endogenous RGS3 in controlling T cell migration in vitro and in an in vivo model of inflammation.

Causal modeling using network ensemble simulations of genetic and gene expression data predicts genes involved in rheumatoid arthritis.

Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. In silico simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86--a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28.

The mode-of-action by network identification (MNI) algorithm: a network biology approach for molecular target identification.

This protocol details the use of the mode-of-action by network identification (MNI) algorithm to identify the gene targets of a drug treatment based on gene-expression data. Investigators might also use the MNI algorithm to identify the gene mediators of a disease or the physiological state of cells and tissues. The MNI algorithm uses a training data set of hundreds of expression profiles to construct a statistical model of gene-regulatory networks in a cell or tissue. The model describes combinatorial influences of genes on one another. The algorithm then uses the model to filter the expression profile of a particular experimental treatment and thereby distinguish the molecular targets or mediators of the treatment response from hundreds of additional genes that also exhibit expression changes. It takes approximately 1 h per run, although run time is significantly affected by the size of the genome and data set.

Evolutionary conservation and selection of human disease gene orthologs in the rat and mouse genomes.

BACKGROUND: Model organisms have contributed substantially to our understanding of the etiology of human disease as well as having assisted with the development of new treatment modalities. The availability of the human, mouse and, most recently, the rat genome sequences now permit the comprehensive investigation of the rodent orthologs of genes associated with human disease. Here, we investigate whether human disease genes differ significantly from their rodent orthologs with respect to their overall levels of conservation and their rates of evolutionary change. RESULTS: Human disease genes are unevenly distributed among human chromosomes and are highly represented (99.5%) among human-rodent ortholog sets. Differences are revealed in evolutionary conservation and selection between different categories of human disease genes. Although selection appears not to have greatly discriminated between disease and non-disease genes, synonymous substitution rates are significantly higher for disease genes. In neurological and malformation syndrome disease systems, associated genes have evolved slowly whereas genes of the immune, hematological and pulmonary disease systems have changed more rapidly. Amino-acid substitutions associated with human inherited disease occur at sites that are more highly conserved than the average; nevertheless, 15 substituting amino acids associated with human disease were identified as wild-type amino acids in the rat. Rodent orthologs of human trinucleotide repeat-expansion disease genes were found to contain substantially fewer of such repeats. Six human genes that share the same characteristics as triplet repeat-expansion disease-associated genes were identified; although four of these genes are expressed in the brain, none is currently known to be associated with disease. CONCLUSIONS: Most human disease genes have been retained in rodent genomes. Synonymous nucleotide substitutions occur at a higher rate in disease genes, a finding that may reflect increased mutation rates in the chromosomal regions in which disease genes are found. Rodent orthologs associated with neurological function exhibit the greatest evolutionary conservation; this suggests that rodent models of human neurological disease are likely to most faithfully represent human disease processes. However, with regard to neurological triplet repeat expansion-associated human disease genes, the contraction, relative to human, of rodent trinucleotide repeats suggests that rodent loci may not achieve a 'critical repeat threshold' necessary to undergo spontaneous pathological repeat expansions. The identification of six genes in this study that have multiple characteristics associated with repeat expansion-disease genes raises the possibility that not all human loci capable of facilitating neurological disease by repeat expansion have as yet been identified.

Identification of potential cell-surface proteins in Candida albicans and investigation of the role of a putative cell-surface glycosidase in adhesion and virulence.

Cell-surface proteins are attractive targets for the development of novel antifungals as they are more accessible to drugs than are intracellular targets. By using a computational biology approach, we identified 180 potential cell-surface proteins in Candida albicans, including the known cell-surface adhesin Als1 and other cell-surface antigens, such as Pra1 and Csa1. Six proteins (named Csf1-6 for cell-surface factors) were selected for further biological characterization. First, we verified that the selected CSF genes are expressed in the yeast and/or hyphal form and then we investigated the effect of the loss of each CSF gene on cell-wall integrity, filamentation, adhesion to mammalian cells and virulence. As a result, we identified Csf4, a putative glycosidase with an apparent orthologue in Saccharomyces cerevisiae (Utr2), as an important factor for cell-wall integrity and maintenance. Interestingly, deletion of CSF4 also resulted in a defect in filamentation, a reduction in adherence to mammalian cells in an in vitro adhesion assay, and a prolongation of survival in an immunocompetent mouse model of disseminated candidiasis. A delay in colonization of key organs (e.g. kidney) was also observed, which is consistent with a reduction in virulence of the csf4-deletion strain. These data indicate a key role for extracellular glycosidases in fungal pathogenesis and represent a new site for therapeutic intervention to cure and prevent fungal disease.