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RATIONALE: Type 2 innate lymphoid cells (ILC2s) are significant sources of type 2 cytokines, which are implicated in the pathogenesis of asthma and asthma exacerbations. The role of ILC2s in virus-induced asthma exacerbations is not well characterized. OBJECTIVES: To characterize pulmonary ILC responses following experimental rhinovirus challenge in patients with moderate asthma and healthy subjects. METHODS: Patients with moderate asthma and healthy subjects were inoculated with rhinovirus-16 and underwent bronchoscopy at baseline and at Day 3, and Day 8 after inoculation. Pulmonary ILC1s and ILC2s were quantified in bronchoalveolar lavage using flow cytometry. The ratio of bronchoalveolar lavage ILC2:ILC1 was assessed to determine their relative contributions to the clinical and immune response to rhinovirus challenge. MEASUREMENTS AND MAIN RESULTS: At baseline, ILC2s were significantly higher in patients with asthma than in healthy subjects. At Day 8, ILC2s significantly increased from baseline in both groups, which was significantly higher in patients with asthma than in healthy subjects (all comparisons P

The signalling receptor for LPS, CD14, is a key marker of, and facilitator for, pro-inflammatory macrophage function. Pro-inflammatory macrophage differentiation remains a process facilitating a broad array of disease pathologies, and has recently emerged as a potential target against cytokine storm in COVID19. Here, we perform a whole-genome CRISPR screen to identify essential nodes regulating CD14 expression in myeloid cells, using the differentiation of THP-1 cells as a starting point. This strategy uncovers many known pathways required for CD14 expression and regulating macrophage differentiation while additionally providing a list of novel targets either promoting or limiting this process. To speed translation of these results, we have then taken the approach of independently validating hits from the screen using well-curated small molecules. In this manner, we identify pharmacologically tractable hits that can either increase CD14 expression on non-differentiated monocytes or prevent CD14 upregulation during macrophage differentiation. An inhibitor for one of these targets, MAP2K3, translates through to studies on primary human monocytes, where it prevents upregulation of CD14 following M-CSF induced differentiation, and pro-inflammatory cytokine production in response to LPS. Therefore, this screening cascade has rapidly identified pharmacologically tractable nodes regulating a critical disease-relevant process.

Spleen tyrosine kinase (SYK) is a protein kinase involved in cell proliferation and the regulation of inflammatory pathways. Due to the increasing evidence that kinase inhibitors have potential as specific anti-inflammatory drugs, we have investigated the potential for SYK inhibition as a therapeutic target in autoimmune diseases, particularly cutaneous lupus erythematosus (CLE). Skin samples of patients with different CLE subtypes and appropriate controls were analysed for the expression of SYK and SYK-associated pro-inflammatory mediators via gene expression analysis and immunohistochemistry. The functional role of SYK in keratinocytes was investigated in vitro, using LE-typical pro-inflammatory stimuli and a selective inhibitor of SYK. SYK-associated genes are strongly upregulated in CLE skin lesions. Importantly, phosphorylated SYK (pSYK) is strongly expressed by several immune cell types and also keratinocytes in CLE skin. In vitro, immunostimulatory nucleic acids are capable of inducing SYK phosphorylation in keratinocytes leading to the induction of pro-inflammatory cytokines, while small-molecule SYK inhibition decreases the expression of these proteins. The results demonstrate that pSYK is expressed by immune cells and keratinocytes in skin lesions of CLE patients. LE-typical stimuli induce the expression of pSYK in vitro. Small-molecule SYK inhibition leads to a reduction of pSYK expression and downregulation of pro-inflammatory cytokines in keratinocytes. We therefore believe that pSYK provides a potential future drug target for the treatment of patients who suffer from CLE and related skin disorders. Specifically, our study reveals evidence supporting the use of topical SYK inhibitors in treating lupus.

Genetic association of polymorphisms in the IL6R gene with severity of asthma, high levels of systemic sIL-6R and poor lung function has been reported (Hawkins et al. JACI 2012; 130:510-5). Higher levels of systemic IL-6 have been shown to be associated with asthma severity, elevated BMI, CRP and blood neutrophils (Peters et al. Lancet Respir Med 2016; 4:574-84). In this study, we investigated whether sputum IL-6 pathway activity is aberrant in a subgroup of asthma patients and is associated with particular clinical characteristics. We used a hypothesis driven analysis by investigating sputum transcriptomics (n=77), sputum and blood proteomics and clinical data from UBIOPRED consortium severe asthma cohort. As asthma is a heterogeneous disease, we used a clustering approach to identify subgroups of patients using genes correlated with IL6R sputum mRNA. The analysis identified two subgroups with high (n=33) and low (n=28) IL6R expression. Mean IL6R expression level in the high IL6R group was 2.8-fold (p This IL6R-high sub-population of severe asthma patients with high sputum neutrophilia has a high unmet need that could potentially benefit from targeting IL-6 pathway.

Background The KMT2A/MLL1 lysine methyltransferase complex is an epigenetic regulator of selected developmental genes, in part through the SET domain-catalysed methylation of H3K4. It is essential for normal embryonic development and haematopoiesis and frequently mutated in cancer. The catalytic properties and targeting of KMT2A/MLL1 depend on the proteins with which it complexes and the post-translational protein modifications which some of these proteins put in place, though detailed mechanisms remain unclear. Results KMT2A/MLL1 (both native and FLAG-tagged) and Msk1 (RPS6KA5) co-immunoprecipitated in various cell types. KMT2A/MLL1 and Msk1 knockdown demonstrated that the great majority of genes whose activity changed on KTM2A/MLL1 knockdown, responded comparably to Msk1 knockdown, as did levels of H3K4 methylation and H3S10 phosphorylation at KTM2A target genes HoxA4, HoxA5. Knockdown experiments also showed that KMT2A/MLL1 is required for the genomic targeting of Msk1, but not vice versa. Conclusion The KMT2A/MLL1 complex is associated with, and functionally dependent upon, the kinase Msk1, part of the MAP kinase signalling pathway. We propose that Msk1-catalysed phosphorylation at H3 serines 10 and 28, supports H3K4 methylation by the KMT2A/MLL1 complex both by making H3 a more attractive substrate for its SET domain, and improving target gene accessibility by prevention of HP1- and Polycomb-mediated chromatin condensation. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0103-3) contains supplementary material, which is available to authorized users.

Furan, a heat-generated food contaminant, is hepatotoxic and carcinogenic in rodents. Furan is oxidized by cytochrome P450 2E1 to cis-2-butene-1,4-dial, a chemically reactive α,β-unsaturated dialdehyde, which has been identified as the key toxic metabolite of furan based on its ability to interact with tissue nucleophiles. In addition to genotoxicity, sustained cytotoxicity mediated through covalent binding of cis-2-butene-1,4-dial to critical target proteins is thought to play a key role in furan carcinogenicity. To identify putative protein targets of reactive furan metabolites, male F344/N rats (n = 5 per dose) were administered a single dose of [3,4-(14)C]-furan (20 mCi/mmol) at doses associated with hepatotoxicity following long-term exposure (0.1 and 2 mg/kg body weight [bw]). Liver proteins were separated by two-dimensional gel electrophoresis and protein spots carrying radiolabel were located by fluorography. In total, 83 discrete protein spots containing (14)C were consistently detected in livers of animals given [3,4-(14)C]-furan at 2.0 mg/kg bw, accounting for 4-5% of the proteome covered by our analyses. Protein spots were excised and digested in gel with trypsin for identification by protein mass spectrometry. Protein database search and subsequent pathway mapping identified 61 proteins localized predominantly in the cytosol and mitochondria, including structural proteins, mitochondrial enzymes involved in glucose metabolism, mitochondrial β-oxidation, and adenosine triphosphate synthesis, and proteins that participate in the maintenance of redox homeostasis and protein folding. Collectively, our data suggest that functional loss of several individual proteins and interference with pathways, most notably mitochondrial energy production, redox regulation, and protein folding, may combine to disrupt cell homeostasis and cause hepatocyte cell death.

An important area of research in systems biology involves the analysis and integration of genome-wide functional datasets. In this context, a major goal is the identification of a putative molecular network controlling physiological response from experimental data. With very fragmentary mechanistic information, this is a challenging task. A number of methods have been developed, each one with the potential to address an aspect of the problem. Here, we review some of the most widely used methodologies and report new results in support of the usefulness of modularization and other modelling techniques in identifying components of the molecular networks that are predictive of physiological response. We also discuss how system identification in biology could be approached, using a combination of methodologies that aim to reconstruct the relationship between molecular pathways and physiology at different levels of the organizational complexity of the molecular network.

Hexose-6-phosphate dehydrogenase (H6PD) is the initial component of a pentose phosphate pathway inside the endoplasmic reticulum (ER) that generates NADPH for ER enzymes. In liver H6PD is required for the 11-oxoreductase activity of 11β-hydroxysteroid dehydrogenase type 1, which converts inactive 11-oxo-glucocorticoids to their active 11-hydroxyl counterparts; consequently, H6PD null mice are relatively insensitive to glucocorticoids, exhibiting fasting hypoglycemia, increased insulin sensitivity despite elevated circulating levels of corticosterone, and increased basal and insulin-stimulated glucose uptake in muscles normally enriched in type II (fast) fibers, which have increased glycogen content. Here, we show that H6PD null mice develop a severe skeletal myopathy characterized by switching of type II to type I (slow) fibers. Running wheel activity and electrically stimulated force generation in isolated skeletal muscle are both markedly reduced. Affected muscles have normal sarcomeric structure at the electron microscopy level but contain large intrafibrillar membranous vacuoles and abnormal triads indicative of defects in structure and function of the sarcoplasmic reticulum (SR). SR proteins involved in calcium metabolism, including the sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA), calreticulin, and calsequestrin, show dysregulated expression. Microarray analysis and real-time PCR demonstrate overexpression of genes encoding proteins in the unfolded protein response pathway. We propose that the absence of H6PD induces a progressive myopathy by altering the SR redox state, thereby impairing protein folding and activating the unfolded protein response pathway. These studies thus define a novel metabolic pathway that links ER stress to skeletal muscle integrity and function.

Gliomas are a highly heterogeneous group of brain tumours that are refractory to treatment, highly invasive and pro-angiogenic. Glioblastoma patients have an average survival time of less than 15 months. Understanding the molecular basis of different grades of glioma, from well differentiated, low-grade tumours to high-grade tumours, is a key step in defining new therapeutic targets. Here we use a data-driven approach to learn the structure of gene regulatory networks from observational data and use the resulting models to formulate hypothesis on the molecular determinants of glioma stage. Remarkably, integration of available knowledge with functional genomics datasets representing clinical and pre-clinical studies reveals important properties within the regulatory circuits controlling low and high-grade glioma. Our analyses first show that low and high-grade gliomas are characterised by a switch in activity of two subsets of Rho GTPases. The first one is involved in maintaining normal glial cell function, while the second is linked to the establishment of multiple hallmarks of cancer. Next, the development and application of a novel data integration methodology reveals novel functions of RND3 in controlling glioma cell migration, invasion, proliferation, angiogenesis and clinical outcome., Author Summary Gliomas are aggressive brain tumours that are invasive, heterogeneous, refractory to treatment and show poor survival rates. Surgical resection and chemotherapy can increase patient survival but ultimately the disease is fatal. Multiple grades of glioma exist, with lower grades associated to better prognosis. While the majority of high-grade gliomas occur de novo, it is common that low-grade gliomas progress to the more aggressive form known as glioblastoma. In this article, we have shown that by combining advanced network biology approaches with the right experimental models, we are able to reveal novel regulatory circuits controlling multiple hallmarks of glioma. Through analysis of multiple network models representing protein-protein interaction or gene co-expression data we have revealed a switch in the role of regulatory Rho GTPases between low and high-grade gliomas. Amongst these, we show that RND3 is up-regulated in glioblastomas and is a key regulator of tumour proliferation, migration and invasion. We confirm that expression and genomic copy number of RND3 are predictive of clinical outcome, suggesting that changes in the activity of this particular Rho GTPase could be an early event associated to transformation and tumour expansion.

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations., Author Summary Understanding how living organisms adapt to changes in their natural habitats is of paramount importance particularly in respect to environmental stressors, such as pollution or climate. Computational models integrating the multi-level molecular responses with organism physiology are likely to be indispensable tools to address this challenge. However, because of the difficulties in acquiring and integrating data from non-model species and because of the intrinsic complexity of field studies, such an approach has not yet been attempted. Here we describe the first example of a global network reconstruction linking transcriptional and metabolic responses to physiology in the flatfish, European flounder, a species currently used to monitor coastal waters around Northern Europe. The model we developed has revealed a remarkable similarity between network modules predictive of chemical exposure in the environment and pathways involved in relevant aspects of human pathophysiology. Generally, the approach we have pioneered has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

Background To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co-ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients., Author Summary Chronic Obstructive Pulmonary Disease (COPD) is a major life threatening disease of the lungs, characterized by airflow limitation and chronic inflammation. Progressive reduction of the body muscle mass is a condition linked to COPD that significantly decreases quality of life and survival. Physical exercise has been proposed as a therapeutic option but its utility is still a matter of debate. The mechanisms underlying muscle wasting are also still largely unknown. The results presented in this paper show that diseased muscles are largely unable to coordinate the expression of muscle remodelling and bioenergetics pathways and that the cause of this phenomena may be tissue hypoxia. These findings contrast with current hypotheses based on the role of chronic inflammation and show that a mechanism based on an oxygen driven, epigenetic control of these two important functions may be an important disease mechanism.