Heme oxygenase-1 protects against Alzheimer’s amyloid-β1-42 induced toxicity via carbon monoxide production

Heme oxygenase-1 (HO-1), an inducible enzyme up-regulated in Alzheimer‟s disease (AD), catabolises heme to biliverdin, Fe2+ and carbon monoxide (CO). CO can protect neurones from oxidative stress-induced apoptosis by inhibiting Kv2.1 channels, which mediate cellular K+ efflux as an early step in the apoptotic cascade. Since apoptosis contributes to the neuronal loss associated with amyloid β peptide (Aβ) toxicity in AD, we investigated the protective effects of HO-1 and CO against Aβ1-42 toxicity in SH-SY5Y cells, employing cells stably transfected with empty vector or expressing the cellular prion protein, PrPc, and rat primary hippocampal neurons. Aβ1-42 (containing protofibrils) caused a concentrationdependent decrease in cell viability, attributable at least in part to induction of apoptosis, with the PrPc expressing cells showing greater susceptibility to Aβ1-42 toxicity. Pharmacological induction or genetic over-expression of HO-1 significantly ameliorated the effects of Aβ1-42. The CO-donor CORM-2 protected cells against Aβ1-42 toxicity in a concentration-dependent manner. Electrophysiological studies revealed no differences in the outward current pre- and post-Aβ1-42 treatment suggesting that K+ channel activity is unaffected in these cells. Instead, Aβ toxicity was reduced by the L-type Ca2+ channel blocker nifedipine, and by the CaMKKII inhibitor, STO-609. Aβ also activated the downstream kinase, AMP-dependent protein kinase (AMPK). CO prevented this activation of AMPK. Our findings indicate that HO-1 protects against Aβ toxicity via production of CO. Protection does not arise from inhibition of apoptosis-associated K+ efflux, but rather by inhibition of AMPK activation, which has been recently implicated in the toxic effects of Aβ. These data provide a novel, beneficial effect of CO which adds to its growing potential as a therapeutic agent.

Evolutionary resurrection of flagellar motility via rewiring of the nitrogen regulation system

A central process in evolution is the recruitment of genes to regulatory networks. We engineered immotile strains of the bacterium Pseudomonas fluorescens that lack flagella due to deletion of the regulatory gene fleQ. Under strong selection for motility, these bacteria consistently regained flagella within 96 hours via a two-step evolutionary pathway. Step 1 mutations increase intracellular levels of phosphorylated NtrC, a distant homologue of FleQ, which begins to commandeer control of the fleQ regulon at the cost of disrupting nitrogen uptake and assimilation. Step 2 is a switch-of-function mutation that redirects NtrC away from nitrogen uptake and towards its novel function as a flagellar regulator. Our results demonstrate that natural selection can rapidly rewire regulatory networks in very few, repeatable mutational steps.

Signaling via NF-kappaB in the nervous system

Nuclear factor kappa B (NF-kappaB) is an inducible transcription factor present in neurons and glia. Recent genetic models identified a role for NF-kappaB in neuroprotection against various neurotoxins. Furthermore, genetic evidence for a role in learning and memory is now emerging. This review highlights our current understanding of neuronal NF-kappaB in response to synaptic transmission and summarizes potential physiological functions of NF-kappaB in the nervous system. This article contains a listing of NF-kappaB activators and inhibitors in the nervous system, furthermore specific target genes are discussed. Synaptic NF-kappaB activated by glutamate and Ca2+ will be presented in the context of retrograde signaling. A controversial role of NF-kappaB in neurodegenerative diseases will be discussed. A model is proposed explaining this paradox as deregulated physiological NF-kappaB activity, where novel results are integrated, showing that p65 could be turned from an activator to a repressor of anti-apoptotic genes.

Tumor necrosis factor alpha triggers proliferation of adult neural stem cells via IKK/NF-kappaB signaling

BACKGROUND: Brain inflammation has been recognized as a complex phenomenon with numerous related aspects. In addition to the very well-described neurodegenerative effect of inflammation, several studies suggest that inflammatory signals exert a potentially positive influence on neural stem cell proliferation, migration and differentiation. Tumor necrosis factor alpha (TNF-alpha) is one of the best-characterized mediators of inflammation. To date, conclusions about the action of TNF on neural stem or progenitor cells (NSCs, NPCs) have been conflicting. TNF seems to activate NSC proliferation and to inhibit their differentiation into NPCs. The purpose of the present study was to analyze the molecular signal transduction mechanisms induced by TNF and resulting in NSC proliferation. RESULTS: Here we describe for the first time the TNF-mediated signal transduction cascade in neural stem cells (NSCs) that results in increased proliferation. Moreover, we demonstrate IKK-alpha/beta-dependent proliferation and markedly up-regulated cyclin D1 expression after TNF treatment. The significant increase in proliferation in TNF-treated cells was indicated by increased neurosphere volume, increased bromodeoxyuridin (BrdU) incorporation and a higher total cell number. Furthermore, TNF strongly activated nuclear factor-kappa B (NF-kappaB) as measured by reporter gene assays and by an activity-specific antibody. Proliferation of control and TNF-treated NSCs was strongly inhibited by expression of the NF-kappaB super-repressor IkappaB-AA1. Pharmacological blockade of IkappaB ubiquitin ligase activity led to comparable decreases in NF-kappaB activity and proliferation. In addition, IKK-beta gene product knock-down via siRNA led to diminished NF-kappaB activity, attenuated cyclin D1 expression and finally decreased proliferation. In contrast, TGFbeta-activated kinase 1 (TAK-1) is partially dispensable for TNF-mediated and endogenous proliferation. Understanding stem cell proliferation is crucial for future regenerative and anti-tumor medicine. CONCLUSION: TNF-mediated activation of IKK-beta resulted in activation of NF-kappaB and was followed by up-regulation of the bona-fide target gene cyclin D1. Activation of the canonical NF-kappaB pathway resulted in strongly increased proliferation of NSCs.

Transcription factor NF-kappaB is transported to the nucleus via cytoplasmic dynein/dynactin motor complex in hippocampal neurons

Background Long-term changes in synaptic plasticity require gene transcription, indicating that signals generated at the synapse must be transported to the nucleus. Synaptic activation of hippocampal neurons is known to trigger retrograde transport of transcription factor NF-κB. Transcription factors of the NF-κB family are widely expressed in the nervous system and regulate expression of several genes involved in neuroplasticity, cell survival, learning and memory. Principal Findings In this study, we examine the role of the dynein/dynactin motor complex in the cellular mechanism targeting and transporting activated NF-κB to the nucleus in response to synaptic stimulation. We demonstrate that overexpression of dynamitin, which is known to dissociate dynein from microtubules, and treatment with microtubule-disrupting drugs inhibits nuclear accumulation of NF-κB p65 and reduces NF-κB-dependent transcription activity. In this line, we show that p65 is associated with components of the dynein/dynactin complex in vivo and in vitro and that the nuclear localization sequence (NLS) within NF-κB p65 is essential for this binding. Conclusion This study shows the molecular mechanism for the retrograde transport of activated NF-κB from distant synaptic sites towards the nucleus.

Effect of pair interactions on transition probabilities between inactive and active states: achieving collective behaviour via pair interactions in social insects

To understand the evolution of well-organized social behaviour, we must first understand the mechanism by which collective behaviour establishes. In this study, the mechanisms of collective behaviour in a colony of social insects were studied in terms of the transition probability between active and inactive states, which is linked to mutual interactions. The active and inactive states of the social insects were statistically extracted from the velocity profiles. From the duration distributions of the two states, we found that 1) the durations of active and inactive states follow an exponential law, and 2) pair interactions increase the transition probability from inactive to active states. The regulation of the transition probability by paired interactions suggests that such interactions control the populations of active and inactive workers in the colony.

Hydrophilic sulfonated bis-1,2,4-triazine ligands are highly effective reagents for separating actinides(iii) from lanthanides(iii) via selective formation of aqueous actinide complexes

We report the first examples of hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine (BTBP) and 2,9-bis(1,2,4-triazin-3-yl)-1,10-phenanthroline (BTPhen) ligands, and their applications as actinide(III) selective aqueous complexing agents. The combination of a hydrophobic diamide ligand in the organic phase and a hydrophilic tetrasulfonated bis-triazine ligand in the aqueous phase is able to separate Am(III) from Eu(III) by selective Am(III) complex formation across a range of nitric acid concentrations with very high selectivities, and without the use of buffers. In contrast, disulfonated bis-triazine ligands are unable to separate Am(III) from Eu(III) in this system. The greater ability of the tetrasulfonated ligands to retain Am(III) selectively in the aqueous phase than the corresponding disulfonated ligands appears to be due to the higher aqueous solubilities of the complexes of the tetrasulfonated ligands with Am(III). The selectivities for Am(III) complexation observed with hydrophilic tetrasulfonated bis-triazine ligands are in many cases far higher than those found with the polyaminocarboxylate ligands previously used as actinide-selective complexing agents, and are comparable to those found with the parent hydrophobic bis-triazine ligands. Thus we demonstrate a feasible alternative method to separate actinides from lanthanides than the widely studied approach of selective actinide extraction with hydrophobic bis-1,2,4-triazine ligands such as CyMe4-BTBP and CyMe4-BTPhen.

Microbial Recognition Via Toll-Like Receptor-Dependent and -Independent Pathways Determines the Cytokine Response of Murine Dendritic Cell Subsets to CD40 Triggering

Dendritic cells (DC) can produce Th-polarizing cytokines and direct the class of the adaptive immune response. Microbial stimuli, cytokines, chemokines, and T cell-derived signals all have been shown to trigger cytokine synthesis by DC, but it remains unclear whether these signals are functionally equivalent and whether they determine the nature of the cytokine produced or simply initiate a preprogrammed pattern of cytokine production, which may be DC subtype specific. Here, we demonstrate that microbial and T cell-derived stimuli can synergize to induce production of high levels of IL-12 p70 or IL-10 by individual murine DC subsets but that the choice of cytokine is dictated by the microbial pattern recognition receptor engaged. We show that bacterial components such as CpG-containing DNA or extracts from Mycobacterium tuberculosis predispose CD8alpha(+) and CD8alpha(-)CD4(-) DC to make IL-12 p70. In contrast, exposure of CD8alpha(+), CD4(+) and CD8alpha(-)CD4(-) DC to heat-killed yeasts leads to production of IL-10. In both cases, secretion of high levels of cytokine requires a second signal from T cells, which can be replaced by CD40 ligand. Consistent with their differential effects on cytokine production, extracts from M. tuberculosis promote IL-12 production primarily via Toll-like receptor 2 and an MyD88-dependent pathway, whereas heat-killed yeasts activate DC via a Toll-like receptor 2-, MyD88-, and Toll/IL-1R domain containing protein-independent pathway. These results show that T cell feedback amplifies innate signals for cytokine production by DC and suggest that pattern recognition rather than ontogeny determines the production of cytokines by individual DC subsets.

A role for adhesion and degranulation-promoting adapter protein in collagen-induced platelet activation mediated via integrin α(2) β(1)

Platelet aggregation and phosphorylation of phospholipase Cγ2 induced by collagen were attenuated in ADAP(-/-) platelets. However, aggregation and signaling induced by collagen-related peptide (CRP), a GPVI-selective agonist, were largely unaffected. Platelet adhesion to CRP was also unaffected by ADAP deficiency. Adhesion to the α(2) β(1) -selective ligand GFOGER and to a peptide (III-04), which supports adhesion that is dependent on both GPVI and α(2) β(1), was reduced in ADAP(-/-) platelets. An impedance-based label-free detection technique, which measures adhesion and spreading of platelets, indicated that, in the absence of ADAP, spreading on GFOGER was also reduced. This was confirmed with non-fluorescent differential-interference contrast microscopy, which revealed reduced filpodia formation in ADAP(-/-) platelets adherent to GFOGER. This indicates that ADAP plays a role in mediating platelet activation via the collagen-binding integrin α(2) β(1). In addition, we found that ADAP(-/-) mice, which are mildly thrombocytopenic, have enlarged spleens as compared with wild-type animals. This may reflect increased removal of platelets from the circulation.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

High-throughput monitoring of wild bee diversity and abundance via mitogenomics

1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline. 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes. 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93�7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R2 = 24�9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline. 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and istributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

Heterogeneous tensor decomposition for clustering via manifold optimization

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.