The alpha 7 nicotinic receptor agonist PHA-543613 hydrochloride inhibits <i>Porphyromonas gingivalis</i>-induced expression of interleukin-8 by oral keratinocytes

Objective: The alpha 7 nicotinic receptor (α7nAChR) is expressed by oral keratinocytes. α7nAChR activation mediates anti-inflammatory responses. The objective of this study was to determine if α7nAChR activation inhibited pathogen-induced interleukin-8 (IL-8) expression by oral keratinocytes.&lt;p&gt;&lt;/p&gt; Materials and methods: Periodontal tissue expression of α7nAChR was determined by real-time PCR. OKF6/TERT-2 oral keratinocytes were exposed to &lt;i&gt;Porphyromonas gingivalis&lt;/i&gt; in the presence and absence of a α7nAChR agonist (PHA-543613 hydrochloride) alone or after pre-exposure to a specific α7nAChR antagonist (α-bungarotoxin). Interleukin-8 (IL-8) expression was measured by ELISA and real-time PCR. Phosphorylation of the NF-κB p65 subunit was determined using an NF-κB p65 profiler assay and STAT-3 activation by STAT-3 in-cell ELISA. The release of ACh from oral keratinocytes in response to &lt;i&gt;P. gingivalis&lt;/i&gt; lipopolysaccharide was determined using a GeneBLAzer M3 CHO-K1-blacell reporter assay.&lt;p&gt;&lt;/p&gt; Results: Expression of α7nAChR mRNA was elevated in diseased periodontal tissue. PHA-543613 hydrochloride inhibited &lt;i&gt;P. Gingivalis&lt;/i&gt;-induced expression of IL-8 at the transcriptional level. This effect was abolished when cells were pre-exposed to a specific α7nAChR antagonist, α-bungarotoxin. PHA-543613 hydrochloride downregulated NF-κB signalling through reduced phosphorylation of the NF-κB p65-subunit. In addition, PHA-543613 hydrochloride promoted STAT-3 signalling by maintenance of phosphorylation. Furthermore, oral keratinocytes upregulated ACh release in response to &lt;i&gt;P. Gingivalis&lt;/i&gt; lipopolysaccharide.&lt;p&gt;&lt;/p&gt; Conclusion: These data suggest that α7nAChR plays a role in regulating the innate immune responses of oral keratinocytes.&lt;p&gt;&lt;/p&gt

A dynamic network approach for the study of human phenotypes

The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure

Depression and sickness behavior are Janus-faced responses to shared inflammatory pathways

It is of considerable translational importance whether depression is a form or a consequence of sickness behavior. Sickness behavior is a behavioral complex induced by infections and immune trauma and mediated by pro-inflammatory cytokines. It is an adaptive response that enhances recovery by conserving energy to combat acute inflammation. There are considerable phenomenological similarities between sickness behavior and depression, for example, behavioral inhibition, anorexia and weight loss, and melancholic (anhedonia), physio-somatic (fatigue, hyperalgesia, malaise), anxiety and neurocognitive symptoms. In clinical depression, however, a transition occurs to sensitization of immuno-inflammatory pathways, progressive damage by oxidative and nitrosative stress to lipids, proteins, and DNA, and autoimmune responses directed against self-epitopes. The latter mechanisms are the substrate of a neuroprogressive process, whereby multiple depressive episodes cause neural tissue damage and consequent functional and cognitive sequelae. Thus, shared immuno-inflammatory pathways underpin the physiology of sickness behavior and the pathophysiology of clinical depression explaining their partially overlapping phenomenology. Inflammation may provoke a Janus-faced response with a good, acute side, generating protective inflammation through sickness behavior and a bad, chronic side, for example, clinical depression, a lifelong disorder with positive feedback loops between (neuro)inflammation and (neuro)degenerative processes following less well defined triggers

p21Waf1 expression is regulated by nuclear intermediate filament vimentin in neuroblastoma

<p>Abstract</p> <p>Background</p> <p>Human neuroblastoma (NB) cell lines may present with either one of the so-called S-and N-subtypes. We have previously reported a strong correlation between protein expression levels of vimentin, an S-subtype marker, and the p21^Waf1cyclin-dependent kinase inhibitor. We here investigated whether this correlation extend to the mRNA level in NB cell lines as well as in patients' tumors. We also further explored the relationship between expression of vimentin and p21, by asking whether vimentin could regulate p21 expression.</p> <p>Methods</p> <p>Vimentin and p21 mRNA levels in NB cell lines as well as in patients' tumors (<it>n </it>= 77) were quantified using Q-PCR. Q-PCR data obtained from tumors of high risk NB patients (<it>n </it>= 40) were analyzed in relation with the overall survival using the Log-rank Kaplan-Meier estimation. siRNA-mediated depletion or overexpression of vimentin in highly or low expressing vimentin cell lines, respectively, followed by protein expression and promoter activation assays were used to assess the role of vimentin in modulating p21 expression.</p> <p>Results</p> <p>We extend the significant correlation between vimentin and p21 expression to the mRNA level in NB cell lines as well as in patients' tumors. Overall survival analysis from Q-PCR data obtained from tumors of high risk patients suggests that lower levels of p21 expression could be associated with a poorer outcome. Our data additionally indicate that the correlation observed between p21 and vimentin expression levels results from p21 transcriptional activity being regulated by vimentin. Indeed, downregulating vimentin resulted in a significant decrease in p21 mRNA and protein expression as well as in p21 promoter activity. Conversely, overexpressing vimentin triggered an increase in p21 promoter activity in cells with a nuclear expression of vimentin.</p> <p>Conclusion</p> <p>Our results suggest that p21 mRNA tumor expression level could represent a refined prognostic factor for high risk NB patients. Our data also show that vimentin regulates p21 transcription; this is the first demonstration of a gene regulating function for this type III-intermediate filament.</p

HIPPIE: Integrating Protein Interaction Networks with Experiment Based Quality Scores

Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

An Integrative -omics Approach to Identify Functional Sub-Networks in Human Colorectal Cancer

Emerging evidence indicates that gene products implicated in human cancers often cluster together in “hot spots” in protein-protein interaction (PPI) networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a “proteomics-first” approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to “seed” a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC) from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC. Cross-classification experiments to predict disease class show excellent performance using only a few sub-networks, underwriting the strength of the proposed approach in discovering relevant and reproducible sub-networks

Prolonged Depression-Like Behavior Caused by Immune Challenge: Influence of Mouse Strain and Social Environment

Immune challenge by bacterial lipopolysaccharide (LPS) causes short-term behavioral changes indicative of depression. The present study sought to explore whether LPS is able to induce long-term changes in depression-related behavior and whether such an effect depends on mouse strain and social context. LPS (0.83 mg/kg) or vehicle was administered intraperitoneally to female CD1 and C57BL/6 mice that were housed singly or in groups of 4. Depression-like behavior was assessed with the forced swim test (FST) 1 and 28 days post-treatment. Group-housed CD1 mice exhibited depression-like behavior 1 day post-LPS, an effect that leveled off during the subsequent 28 days, while the behavior of singly housed CD1 mice was little affected. In contrast, singly housed C57BL/6 mice responded to LPS with an increase in depression-like behavior that was maintained for 4 weeks post-treatment and confirmed by the sucrose preference test. Group-housed C57BL/6 mice likewise displayed an increased depression-like behavior 4 weeks post-treatment. The behavioral changes induced by LPS in C57BL/6 mice were associated with a particularly pronounced rise of interleukin-6 in blood plasma within 1 day post-treatment and with changes in the dynamics of the corticosterone response to the FST. The current data demonstrate that immune challenge with LPS is able to induce prolonged depression-like behavior, an effect that depends on genetic background (strain). The discovery of an experimental model of long-term depression-like behavior after acute immune challenge is of relevance to the analysis of the epigenetic and pathophysiologic mechanisms of immune system-related affective disorders

Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner

Spleen Vagal Denervation Inhibits the Production of Antibodies to Circulating Antigens

BACKGROUND: Recently the vagal output of the central nervous system has been shown to suppress the innate immune defense to pathogens. Here we investigated by anatomical and physiological techniques the communication of the brain with the spleen and provided evidence that the brain has the capacity to stimulate the production of antigen specific antibodies by its parasympathetic autonomic output. METHODOLOGY/PRINCIPAL FINDINGS: This conclusion was reached by successively demonstrating that: 1. The spleen receives not only sympathetic input but also parasympathetic input. 2. Intravenous trinitrophenyl-ovalbumin (TNP-OVA) does not activate the brain and does not induce an immune response. 3. Intravenous TNP-OVA with an inducer of inflammation; lipopolysaccharide (LPS), activates the brain and induces TNP-specific IgM. 4. LPS activated neurons are in the same areas of the brain as those that provide parasympathetic autonomic information to the spleen, suggesting a feed back circuit between brain and immune system. Consequently we investigated the interaction of the brain with the spleen and observed that specific parasympathetic denervation but not sympathetic denervation of the spleen eliminates the LPS-induced antibody response to TNP-OVA. CONCLUSIONS/SIGNIFICANCE: These findings not only show that the brain can stimulate antibody production by its autonomic output, it also suggests that the power of LPS as adjuvant to stimulate antibody production may also depend on its capacity to activate the brain. The role of the autonomic nervous system in the stimulation of the adaptive immune response may explain why mood and sleep have an influence on antibody production