Human Mas-related G protein-coupled receptors-X1 induce chemokine receptor 2 expression in rat dorsal root ganglia neurons and release of chemokine ligand 2 from the human LAD-2 mast cell line

Primate-specific Mas-related G protein-coupled receptors-X1 (MRGPR-X1) are highly enriched in dorsal root ganglia (DRG) neurons and induce acute pain. Herein, we analyzed effects of MRGPR-X1 on serum response factors (SRF) or nuclear factors of activated T cells (NFAT), which control expression of various markers of chronic pain. Using HEK293, DRG neuron-derived F11 cells and cultured rat DRG neurons recombinantly expressing human MRGPR-X1, we found activation of a SRF reporter gene construct and induction of the early growth response protein-1 via extracellular signal-regulated kinases-1/2 known to play a significant role in the development of inflammatory pain. Furthermore, we observed MRGPR-X1-induced up-regulation of the chemokine receptor 2 (CCR2) via NFAT, which is considered as a key event in the onset of neuropathic pain and, so far, has not yet been described for any endogenous neuropeptide. Up-regulation of CCR2 is often associated with increased release of its endogenous agonist chemokine ligand 2 (CCL2). We also found MRGPR-X1-promoted release of CCL2 in a human connective tissue mast cell line endogenously expressing MRGPR-X1. Thus, we provide first evidence to suggest that MRGPR-X1 induce expression of chronic pain markers in DRG neurons and propose a so far unidentified signaling circuit that enhances chemokine signaling by acting on two distinct yet functionally co-operating cell types. Given the important role of chemokine signaling in pain chronification, we propose that interruption of this signaling circuit might be a promising new strategy to alleviate chemokine-promoted pain

ELK1 Uses Different DNA Binding Modes to Regulate Functionally Distinct Classes of Target Genes

Eukaryotic transcription factors are grouped into families and, due to their similar DNA binding domains, often have the potential to bind to the same genomic regions. This can lead to redundancy at the level of DNA binding, and mechanisms are required to generate specific functional outcomes that enable distinct gene expression programmes to be controlled by a particular transcription factor. Here we used ChIP–seq to uncover two distinct binding modes for the ETS transcription factor ELK1. In one mode, other ETS transcription factors can bind regulatory regions in a redundant fashion; in the second, ELK1 binds in a unique fashion to another set of genomic targets. Each binding mode is associated with different binding site features and also distinct regulatory outcomes. Furthermore, the type of binding mode also determines the control of functionally distinct subclasses of genes and hence the phenotypic response elicited. This is demonstrated for the unique binding mode where a novel role for ELK1 in controlling cell migration is revealed. We have therefore uncovered an unexpected link between the type of binding mode employed by a transcription factor, the subsequent gene regulatory mechanisms used, and the functional categories of target genes controlled

Bone turnover markers for early detection of fracture healing disturbances: A review of the scientific literature

Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome.As técnicas imagiológicas são o método convencional para a avaliação dos processos de cicatrização das fraturas. No entanto, estes métodos não são talvez totalmente confiáveis para a deteção precoce de complicações, as mais frequentes destas sendo o atraso da união e a não-união. Um diagnóstico eficaz destas desordens poderia prevenir a dor e a incapacidade prolongada do paciente. Esforços devem ser dirigidos no sentido do desenvolvimento de novas tecnologias para melhorar a exatidão no diagnóstico de complicações após fraturas ósseas. A variação nos níveis dos marcadores do turnover ósseo (BTMs) têm sido avaliados com vista à sua capacidade para prever o comprometimento da cicatrização das fraturas numa fase inicial, no entanto, as conclusões de alguns estudos não são consensuais. Neste artigo os autores fizeram uma revisão do potencial dos BTMs como fatores de previsibilidade precoce do prognóstico em doentes adultos que apresentavam fraturas ósseas traumáticas mas que não sofriam de osteopenia ou osteoporose pós-menopausa. A informação disponível nos diferentes estudos realizados neste campo foi sistematizada com vista a evidenciar-se os BTMs mais promissores para a avaliação da evolução da cicatrização das fraturas.SFRH/BD/45018/200

Serum Response Factor Regulates Immediate Early Host Gene Expression in Toxoplasma gondii-Infected Host Cells

Toxoplasma gondii is a wide spread pathogen that can cause severe and even fatal disease in fetuses and immune-compromised hosts. As an obligate intracellular parasite, Toxoplasma must alter the environment of its host cell in order to establish its replicative niche. This is accomplished, in part, by secretion of factors into the host cell that act to modulate processes such as transcription. Previous studies demonstrated that genes encoding transcription factors such as c-jun, junB, EGR1, and EGR2 were amongst the host genes that were the most rapidly upregulated following infection. In cells stimulated with growth factors, these genes are regulated by a transcription factor named Serum Response Factor. Serum Response Factor is a ubiquitously expressed DNA binding protein that regulates growth and actin cytoskeleton genes via MAP kinase or actin cytoskeletal signaling, respectively. Here, we report that Toxoplasma infection leads to the rapid activation of Serum Response Factor. Serum Response Factor activation is a Toxoplasma-specific event since the transcription factor is not activated by the closely related protozoan parasite, Neospora caninum. We further demonstrate that Serum Response Factor activation requires a parasite-derived secreted factor that signals via host MAP kinases but independently of the host actin cytoskeleton. Together, these data define Serum Response Factor as a host cell transcription factor that regulates immediate early gene expression in Toxoplasma-infected cells

Analysing Change: Complex Rather than Dialectical?

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This article offers a discussion of dialectics from a complexity perspective. Dialectics is a term much utilized but infrequently defined. This article suggests that a spectrum of ideas exist concerning understandings of dialectics. We are particularly critical of Hegelian dialectics, which we see as anthropocentric and teleological. While Marxist approaches to dialectics, in the form of historical materialism, marked a break from the idealist elements of Hegelian dialectics, they retained traces of this approach. The article offers a partial discussion of essential elements of dialectics, which we consider to be the analysis of change, the centrality of contradiction, and the methodology of abstraction. Points of overlap with complexity thinking are highlighted, together with those points where complexity thinking and dialectical approaches diverge. We conclude with some suggestions as to how complexity thinking might contribute to a development of dialectical approaches

Precise Regulation of Gene Expression Dynamics Favors Complex Promoter Architectures

Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure

A selective eradication of human nonhereditary breast cancer cells by phenanthridine-derived polyADP-ribose polymerase inhibitors

INTRODUCTION: PARP-1 (polyADP-ribose polymerase-1) is known to be activated in response to DNA damage, and activated PARP-1 promotes DNA repair. However, a recently disclosed alternative mechanism of PARP-1 activation by phosphorylated externally regulated kinase (ERK) implicates PARP-1 in a vast number of signal-transduction networks in the cell. Here, PARP-1 activation was examined for its possible effects on cell proliferation in both normal and malignant cells. METHODS: In vitro (cell cultures) and in vivo (xenotransplants) experiments were performed. RESULTS: Phenanthridine-derived PARP inhibitors interfered with cell proliferation by causing G2/M arrest in both normal (human epithelial cells MCF10A and mouse embryonic fibroblasts) and human breast cancer cells MCF-7 and MDA231. However, whereas the normal cells were only transiently arrested, G2/M arrest in the malignant breast cancer cells was permanent and was accompanied by a massive cell death. In accordance, treatment with a phenanthridine-derived PARP inhibitor prevented the development of MCF-7 and MDA231 xenotransplants in female nude mice. Quiescent cells (neurons and cardiomyocytes) are not impaired by these PARP inhibitors. CONCLUSIONS: These results outline a new therapeutic approach for a selective eradication of abundant nonhereditary human breast cancers

Modelling survival : exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans

pcaGoPromoter - An R Package for Biological and Regulatory Interpretation of Principal Components in Genome-Wide Gene Expression Data

Analyzing data obtained from genome-wide gene expression experiments is challenging due to the quantity of variables, the need for multivariate analyses, and the demands of managing large amounts of data. Here we present the R package pcaGoPromoter, which facilitates the interpretation of genome-wide expression data and overcomes the aforementioned problems. In the first step, principal component analysis (PCA) is applied to survey any differences between experiments and possible groupings. The next step is the interpretation of the principal components with respect to both biological function and regulation by predicted transcription factor binding sites. The robustness of the results is evaluated using cross-validation, and illustrative plots of PCA scores and gene ontology terms are available. pcaGoPromoter works with any platform that uses gene symbols or Entrez IDs as probe identifiers. In addition, support for several popular Affymetrix GeneChip platforms is provided. To illustrate the features of the pcaGoPromoter package a serum stimulation experiment was performed and the genome-wide gene expression in the resulting samples was profiled using the Affymetrix Human Genome U133 Plus 2.0 chip. Array data were analyzed using pcaGoPromoter package tools, resulting in a clear separation of the experiments into three groups: controls, serum only and serum with inhibitor. Functional annotation of the axes in the PCA score plot showed the expected serum-promoted biological processes, e.g., cell cycle progression and the predicted involvement of expected transcription factors, including E2F. In addition, unexpected results, e.g., cholesterol synthesis in serum-depleted cells and NF-κB activation in inhibitor treated cells, were noted. In summary, the pcaGoPromoter R package provides a collection of tools for analyzing gene expression data. These tools give an overview of the input data via PCA, functional interpretation by gene ontology terms (biological processes), and an indication of the involvement of possible transcription factors