Structural basis for ligase-specific conjugation of linear ubiquitin chains by HOIP

Linear ubiquitin chains are important regulators of cellular signaling pathways that control innate immunity and inflammation through NF-κB activation and protection against TNFα-induced apoptosis(1-5). They are synthesized by HOIP, which belongs to the RBR (RING-between-RING) family of E3 ligases and is the catalytic component of LUBAC (linear ubiquitin chain assembly complex), a multi-subunit E3 ligase(6). RBR family members act as RING/HECT hybrids, employing RING1 to recognize ubiquitin-loaded E2 while a conserved cysteine in RING2 subsequently forms a thioester intermediate with the transferred or “donor” ubiquitin(7). Here we report the crystal structure of the catalytic core of HOIP in its apo form and in complex with ubiquitin. The C-terminal portion of HOIP adopts a novel fold that, together with a zinc finger, forms an ubiquitin-binding platform which orients the acceptor ubiquitin and positions its α-amino group for nucleophilic attack on the E3~ubiquitin thioester. The carboxy-terminal tail of a second ubiquitin molecule is located in close proximity to the catalytic cysteine providing a unique snapshot of the ubiquitin transfer complex containing both donor and acceptor ubiquitin. These interactions are required for activation of the NF-kB pathway in vivo and explain the determinants of linear ubiquitin chain specificity by LUBAC

A dominant function of p38 mitogen-activated protein kinase signaling in receptor activator of nuclear factor-κB ligand expression and osteoclastogenesis induction by Aggregatibacter actinomycetemcomitans and Escherichia coli lipopolysaccharide

Lipopolysaccharide from gram-negative bacteria is one of the microbial-associated molecular patterns that initiate the immune/inflammatory response, leading to the tissue destruction observed in periodontitis. The aim of this study was to evaluate the role of the p38 mitogen-activated protein kinase (MAPK) signaling pathway in lipopolysaccharide-induced receptor activator of nuclear factor-κB ligand (RANKL) expression by murine periodontal ligament cells. Material and Methods:  Expression of RANKL and osteoprotegerin mRNA was studied by reverse transcription-polymerase chain reaction upon stimulation with lipopolysaccharide from Escherichia coli and Aggregatibacter actinomycetemcomitans . The biochemical inhibitor SB203580 was used to evaluate the contribution of the p38 MAPK signaling pathway to lipopolysaccharide-induced RANKL and osteoprotegerin expression. Stable cell lines expressing dominant-negative forms of MAPK kinase (MKK)-3 and MKK6 were generated to confirm the role of the p38 MAPK pathway. An osteoclastogenesis assay using a coculture model of the murine monocytic cell line RAW 264.7 was used to determine if osteoclast differentiation induced by lipopolysaccharide-stimulated periodontal ligament was correlated with RANKL expression. Results:  Inhibiting p38 MAPK prior to lipopolysaccharide stimulation resulted in a significant decrease of RANKL mRNA expression. Osteoprotegerin mRNA expression was not affected by lipopolysaccharide or p38 MAPK. Lipopolysaccharide-stimulated periodontal ligament cells increased osteoclast differentiation, an effect that was completely blocked by osteoprotegerin and significantly decreased by inhibition of MKK3 and MKK6, upstream activators of p38 MAPK. Conditioned medium from murine periodontal ligament cultures did not increase osteoclast differentiation, indicating that periodontal ligament cells produced membrane-bound RANKL. Conclusion:  Lipopolysaccharide resulted in a significant increase of RANKL in periodontal ligament cells. The p38 MAPK pathway is required for lipopolysaccharide-induced membrane-bound RANKL expression in these cells.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65788/1/j.1600-0765.2007.01013.x.pd

The Nexus Solutions Tool (NEST): An open platform for optimizing multi-scale energy-water-land system transformations

The energy-water-land nexus represents a critical leverage future policies must draw upon to reduce trade-offs between sustainable development objectives. Yet, existing long-term planning tools do not provide the scope or level of integration across the nexus to unravel important development constraints. Moreover, existing tools and data are not always made openly available or are implemented across disparate modeling platforms that can be difficult to link directly with modern scientific computing tools and databases. In this paper, we present the Nexus Solutions Tool (NEST): a new open modeling platform that integrates multi-scale energy-water-land resource optimization with distributed hydrological modeling. The new approach provides insights into the vulnerability of water, energy and land resources to future socioeconomic and climatic change and how multi-sectoral policies, technological solutions and investments can improve the resilience and sustainability of transformation pathways while avoiding counterproductive interactions among sectors. NEST can be applied at different spatial and temporal resolutions, and is designed specifically to tap into the growing body of open access geospatial data available through national inventories and the earth system modeling community. A case study analysis of the Indus River Basin in South Asia demonstrates the capability of the model to capture important interlinkages across system transformation pathways towards the United Nations' Sustainable Development Goals, including the intersections between local and regional transboundary policies and incremental investment costs from rapidly increasing regional consumption projected over the coming decades

Principal component and factor analytic models in international sire evaluation

<p>Abstract</p> <p>Background</p> <p>Interbull is a non-profit organization that provides internationally comparable breeding values for globalized dairy cattle breeding programmes. Due to different trait definitions and models for genetic evaluation between countries, each biological trait is treated as a different trait in each of the participating countries. This yields a genetic covariance matrix of dimension equal to the number of countries which typically involves high genetic correlations between countries. This gives rise to several problems such as over-parameterized models and increased sampling variances, if genetic (co)variance matrices are considered to be unstructured.</p> <p>Methods</p> <p>Principal component (PC) and factor analytic (FA) models allow highly parsimonious representations of the (co)variance matrix compared to the standard multi-trait model and have, therefore, attracted considerable interest for their potential to ease the burden of the estimation process for multiple-trait across country evaluation (MACE). This study evaluated the utility of PC and FA models to estimate variance components and to predict breeding values for MACE for protein yield. This was tested using a dataset comprising Holstein bull evaluations obtained in 2007 from 25 countries.</p> <p>Results</p> <p>In total, 19 principal components or nine factors were needed to explain the genetic variation in the test dataset. Estimates of the genetic parameters under the optimal fit were almost identical for the two approaches. Furthermore, the results were in a good agreement with those obtained from the full rank model and with those provided by Interbull. The estimation time was shortest for models fitting the optimal number of parameters and prolonged when under- or over-parameterized models were applied. Correlations between estimated breeding values (EBV) from the PC19 and PC25 were unity. With few exceptions, correlations between EBV obtained using FA and PC approaches under the optimal fit were ≥ 0.99. For both approaches, EBV correlations decreased when the optimal model and models fitting too few parameters were compared.</p> <p>Conclusions</p> <p>Genetic parameters from the PC and FA approaches were very similar when the optimal number of principal components or factors was fitted. Over-fitting increased estimation time and standard errors of the estimates but did not affect the estimates of genetic correlations or the predictions of breeding values, whereas fitting too few parameters affected bull rankings in different countries.</p

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP

Transmission characteristics of heterozygous cases of Creutzfeldt-Jakob disease with variable abnormal prion protein allotypes

In the human prion disease Creutzfeldt-Jakob disease (CJD), different CJD neuropathological subtypes are defined by the presence in normal prion protein (PrPC) of a methionine or valine at residue 129, by the molecular mass of the infectious prion protein PrPSc, by the pattern of PrPSc deposition, and by the distribution of spongiform change in the brain. Heterozygous cases of CJD potentially add another layer of complexity to defining CJD subtypes since PrPSc can have either a methionine (PrPSc-M129) or valine (PrPSc-V129) at residue 129. We have recently demonstrated that the relative amount of PrPSc-M129 versus PrPSc-V129, i.e. the PrPSc allotype ratio, varies between heterozygous CJD cases. In order to determine if differences in PrPSc allotype correlated with different disease phenotypes, we have inoculated 10 cases of heterozygous CJD (7 sporadic and 3 iatrogenic) into two transgenic mouse lines overexpressing PrPC with a methionine at codon 129. In one case, brain-region specific differences in PrPSc allotype appeared to correlate with differences in prion disease transmission and phenotype. In the other 9 cases inoculated, the presence of PrPSc-V129 was associated with plaque formation but differences in PrPSc allotype did not consistently correlate with disease incubation time or neuropathology. Thus, while the PrPSc allotype ratio may contribute to diverse prion phenotypes within a single brain, it does not appear to be a primary determinative factor of disease phenotype

Epigenetic Activation of a Subset of mRNAs by eIF4E Explains Its Effects on Cell Proliferation

BACKGROUND: Translation deregulation is an important mechanism that causes aberrant cell growth, proliferation and survival. eIF4E, the mRNA 5′ cap-binding protein, plays a major role in translational control. To understand how eIF4E affects cell proliferation and survival, we studied mRNA targets that are translationally responsive to eIF4E. METHODOLOGY/PRINCIPAL FINDINGS: Microarray analysis of polysomal mRNA from an eIF4E-inducible NIH 3T3 cell line was performed. Inducible expression of eIF4E resulted in increased translation of defined sets of mRNAs. Many of the mRNAs are novel targets, including those that encode large- and small-subunit ribosomal proteins and cell growth-related factors. In addition, there was augmented translation of mRNAs encoding anti-apoptotic proteins, which conferred resistance to endoplasmic reticulum-mediated apoptosis. CONCLUSIONS/SIGNIFICANCE: Our results shed new light on the mechanisms by which eIF4E prevents apoptosis and transforms cells. Downregulation of eIF4E and its downstream targets is a potential therapeutic option for the development of novel anti-cancer drugs

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis

Functional Interactions between the erupted/tsg101 Growth Suppressor Gene and the DaPKC and rbf1 Genes in Drosophila Imaginal Disc Tumors

BACKGROUND: The Drosophila gene erupted (ept) encodes the fly homolog of human Tumor Susceptibility Gene-101 (TSG101), which functions as part of the conserved ESCRT-1 complex to facilitate the movement of cargoes through the endolysosomal pathway. Loss of ept or other genes that encode components of the endocytic machinery (e.g. synatxin7/avalanche, rab5, and vps25) produces disorganized overgrowth of imaginal disc tissue. Excess cell division is postulated to be a primary cause of these 'neoplastic' phenotypes, but the autonomous effect of these mutations on cell cycle control has not been examined. PRINCIPAL FINDINGS: Here we show that disc cells lacking ept function display an altered cell cycle profile indicative of deregulated progression through the G1-to-S phase transition and express reduced levels of the tumor suppressor ortholog and G1/S inhibitor Rbf1. Genetic reductions of the Drosophila aPKC kinase (DaPKC), which has been shown to promote tumor growth in other fly tumor models, prevent both the ept neoplastic phenotype and the reduction in Rbf1 levels that otherwise occurs in clones of ept mutant cells; this effect is coincident with changes in localization of Notch and Crumbs, two proteins whose sorting is altered in ept mutant cells. The effect on Rbf1 can also be blocked by removal of the gamma-secretase component presenilin, suggesting that cleavage of a gamma-secretase target influences Rbf1 levels in ept mutant cells. Expression of exogenous rbf1 completely ablates ept mutant eye tissues but only mildly affects the development of discs composed of cells with wild type ept. CONCLUSIONS: Together, these data show that loss of ept alters nuclear cell cycle control in developing imaginal discs and identify the DaPKC, presenilin, and rbf1 genes as modifiers of molecular and cellular phenotypes that result from loss of ept