Two step activation of FOXO3 by AMPK generates a coherent feed-forward loop determining excitotoxic cell fate

Cerebral ischemia and excitotoxic injury induce transient or permanent bioenergetic failure, and may result in neuronal apoptosis or necrosis. We have previously shown that ATP depletion and activation of AMP-activated protein kinase (AMPK) during excitotoxic injury induces neuronal apoptosis by transcription of the proapoptotic BH3 only protein, Bim. AMPK, however, also exerts pro-survival functions in neurons. The molecular switches that determine these differential outcomes are not well understood. Using an approach combining biochemistry, single cell imaging and computational modeling, we here demonstrate that excitotoxic injury activated the bim promoter in a FOXO3-dependent manner. The activation of AMPK reduced AKT activation, and led to dephosphorylation and nuclear translocation of FOXO3. Subsequent mutation studies indicated that bim gene activation during excitotoxic injury required direct FOXO3 phosphorylation by AMPK in the nucleus as a second activation step. Inhibition of this phosphorylation prevented Bim expression and protected neurons against excitotoxic and oxygen/glucose deprivation-induced injury. Systems analysis and computational modeling revealed that these two activation steps defined a coherent feedforward loop; a network motif capable of filtering any effects of short-term AMPK activation on bim gene induction. This may prevent unwanted AMPK-mediated Bim expression and apoptosis during transient or physiological bioenergetic stress

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

Trade-offs and Noise Tolerance in Signal Detection by Genetic Circuits

Genetic circuits can implement elaborated tasks of amplitude or frequency signal detection. What type of constraints could circuits experience in the performance of these tasks, and how are they affected by molecular noise? Here, we consider a simple detection process–a signal acting on a two-component module–to analyze these issues. We show that the presence of a feedback interaction in the detection module imposes a trade-off on amplitude and frequency detection, whose intensity depends on feedback strength. A direct interaction between the signal and the output species, in a type of feed-forward loop architecture, greatly modifies these trade-offs. Indeed, we observe that coherent feed-forward loops can act simultaneously as good frequency and amplitude noise-tolerant detectors. Alternatively, incoherent feed-forward loop structures can work as high-pass filters improving high frequency detection, and reaching noise tolerance by means of noise filtering. Analysis of experimental data from several specific coherent and incoherent feed-forward loops shows that these properties can be realized in a natural context. Overall, our results emphasize the limits imposed by circuit structure on its characteristic stimulus response, the functional plasticity of coherent feed-forward loops, and the seemingly paradoxical advantage of improving signal detection with noisy circuit components

IL-17 Expression in the Time Course of Acute Anti-Thy1 Glomerulonephritis

Background Interleukin-17 (IL-17) is a new pro-inflammatory cytokine involved in immune response and inflammatory disease. The main source of IL-17 is a subset of CD4+ T-helper cells, but is also secreted by non-immune cells. The present study analyzes expression of IL-17 in the time course of acute anti- thy1 glomerulonephritis and the role of IL-17 as a potential link between inflammation and fibrosis. Methods Anti-thy1 glomerulonephritis was induced into male Wistar rats by OX-7 antibody injection. After that, samples were taken on days 1, 5, 10 (matrix expansion phase), 15 and 20 (resolution phase). PBS-injected animals served as controls. Proteinuria and histological matrixes score served as the main markers for disease severity. In in vitro experiments, NRK-52E cells were used. For cytokine expressions, mRNA and protein levels were analyzed by utilizing RT-PCR, in situ hybridization and immunofluorescence. Results Highest IL-17 mRNA-expression (6.50-fold vs. con; p<0.05) was found on day 5 after induction of anti-thy1 glomerulonephritis along the maximum levels of proteinuria (113 ± 13 mg/d; p<0.001), histological glomerular-matrix accumulation (82%; p<0.001) and TGF-β1 (2.2-fold; p<0.05), IL-6 mRNA expression (36-fold; p<0.05). IL-17 protein expression co-localized with the endothelial cell marker PECAM in immunofluorescence. In NRK-52E cells, co-administration of TGF-β1 and IL-6 synergistically up-regulated IL-17 mRNA 4986-fold (p<0.001). Conclusions The pro-inflammatory cytokine IL-17 is up-regulated in endothelial cells during the time course of acute anti-thy1 glomerulonephritis. In vitro, NRK-52E cells secrete IL-17 under pro-fibrotic and pro-inflammatory conditions

Diversity Effects on Productivity Are Stronger within than between Trophic Groups in the Arbuscular Mycorrhizal Symbiosis

The diversity of plants and arbuscular mycorrhizal fungi (AMF) has been experimentally shown to alter plant and AMF productivity. However, little is known about how plant and AMF diversity interact to shape their respective productivity.We co-manipulated the diversity of both AMF and plant communities in two greenhouse studies to determine whether the productivity of each trophic group is mainly influenced by plant or AMF diversity, respectively, and whether there is any interaction between plant and fungal diversity. In both experiments we compared the productivity of three different plant species monocultures, or their respective 3-species mixtures. Similarly, in both studies these plant treatments were crossed with an AMF diversity gradient that ranged from zero (non-mycorrhizal controls) to a maximum of three and five taxonomically distinct AMF taxa, respectively. We found that within both trophic groups productivity was significantly influenced by taxon identity, and increased with taxon richness. These main effects of AMF and plant diversity on their respective productivities did not depend on each other, even though we detected significant individual taxon effects across trophic groups.Our results indicate that similar ecological processes regulate diversity-productivity relationships within trophic groups. However, productivity-diversity relationships are not necessarily correlated across interacting trophic levels, leading to asymmetries and possible biotic feedbacks. Thus, biotic interactions within and across trophic groups should be considered in predictive models of community assembly

Monotone and near-monotone biochemical networks

Monotone subsystems have appealing properties as components of larger networks, since they exhibit robust dynamical stability and predictability of responses to perturbations. This suggests that natural biological systems may have evolved to be, if not monotone, at least close to monotone in the sense of being decomposable into a “small” number of monotone components, In addition, recent research has shown that much insight can be attained from decomposing networks into monotone subsystems and the analysis of the resulting interconnections using tools from control theory. This paper provides an expository introduction to monotone systems and their interconnections, describing the basic concepts and some of the main mathematical results in a largely informal fashion

Impact of Dietary Gluten on Regulatory T Cells and Th17 Cells in BALB/c Mice

Dietary gluten influences the development of type 1 diabetes (T1D) and a gluten-free (GF) diet has a protective effect on the development of T1D. Gluten may influence T1D due to its direct effect on intestinal immunity; however, these mechanisms have not been adequately studied. We studied the effect of a GF diet compared to a gluten-containing standard (STD) diet on selected T cell subsets, associated with regulatory functions as well as proinflammatory Th17 cells, in BALB/c mice. Furthermore, we assessed diet-induced changes in the expression of various T cell markers, and determined if changes were confined to intestinal or non-intestinal lymphoid compartments. The gluten-containing STD diet led to a significantly decreased proportion of γδ T cells in all lymphoid compartments studied, although an increase was detected in some γδ T cell subsets (CD8+, CD103+). Further, it decreased the proportion of CD4+CD62L+ T cells in Peyer's patches. Interestingly, no diet-induced changes were found among CD4+Foxp3+ T cells or CD3+CD49b+cells (NKT cells) and CD3−CD49b+ (NK) cells. Mice fed the STD diet showed increased proportions of CD4+CD45RBhigh+ and CD103+ T cells and a lower proportion of CD4+CD45RBlow+ T cells in both mucosal and non-mucosal compartments. The Th17 cell population, associated with the development of autoimmunity, was substantially increased in pancreatic lymph nodes of mice fed the STD diet. Collectively, our data indicate that dietary gluten influences multiple regulatory T cell subsets as well as Th17 cells in mucosal lymphoid tissue while fewer differences were observed in non-mucosal lymphoid compartments

Coordinated Regulation of Virulence during Systemic Infection of Salmonella enterica Serovar Typhimurium

To cause a systemic infection, Salmonella must respond to many environmental cues during mouse infection and express specific subsets of genes in a temporal and spatial manner, but the regulatory pathways are poorly established. To unravel how micro-environmental signals are processed and integrated into coordinated action, we constructed in-frame non-polar deletions of 83 regulators inferred to play a role in Salmonella enteriditis Typhimurium (STM) virulence and tested them in three virulence assays (intraperitoneal [i.p.], and intragastric [i.g.] infection in BALB/c mice, and persistence in 129X1/SvJ mice). Overall, 35 regulators were identified whose absence attenuated virulence in at least one assay, and of those, 14 regulators were required for systemic mouse infection, the most stringent virulence assay. As a first step towards understanding the interplay between a pathogen and its host from a systems biology standpoint, we focused on these 14 genes. Transcriptional profiles were obtained for deletions of each of these 14 regulators grown under four different environmental conditions. These results, as well as publicly available transcriptional profiles, were analyzed using both network inference and cluster analysis algorithms. The analysis predicts a regulatory network in which all 14 regulators control the same set of genes necessary for Salmonella to cause systemic infection. We tested the regulatory model by expressing a subset of the regulators in trans and monitoring transcription of 7 known virulence factors located within Salmonella pathogenicity island 2 (SPI-2). These experiments validated the regulatory model and showed that the response regulator SsrB and the MarR type regulator, SlyA, are the terminal regulators in a cascade that integrates multiple signals. Furthermore, experiments to demonstrate epistatic relationships showed that SsrB can replace SlyA and, in some cases, SlyA can replace SsrB for expression of SPI-2 encoded virulence factors