Interaction of yeast eIF4G with spliceosome components Implications in pre-mRNA processing events

International audienceAs evidenced from mammalian cells the eukaryotic translation initiation factor eIF4G has a putative role in nuclear RNA metabolism. Here we investigate whether this role is conserved in the yeast Saccharomyces cerevisiae. Using a combination of in vitro and in vivo methods, we show that, similar to mammalian eIF4G, yeast eIF4G homologues, Tif4631p and Tif4632p, are present both in the nucleus and the cytoplasm. We show that both eIF4G proteins interact efficiently in vitro with UsnRNP components of the splicing machinery. More specifically, Tif4631p and Tif4632p interact efficiently with U1 snRNA in vitro. In addition, Tif4631p and Tif4632p associate with protein components of the splicing machinery, namely Snu71p and Prp11p. To further delineate these interactions, we map the regions of Tif4631p and Tif4632p that are important for the interaction with Prp11p and Snu71p and we show that addition of these regions to splicing reactions in vitro has a dominant inhibitory effect. The observed interactions implicate eIF4G in aspects of pre-mRNA processing. In support of this hypothesis, deletion of one of the eIF4G isoforms results in accumulation of un-spliced precursors for a number of endogenous genes, in vivo. In conclusion these observations are suggestive of the involvement of yeast eIF4G in pre-mRNA metabolism

Leukopenia Associated with Long-Term Colchicine Adminsitration

Purpose A case of leukopenia in a patient receiving colchicine for calcium pyrophosphate dihydrate deposition disease, or pseudogout, is reported. Summary An 85-year-old man experienced leukopenia likely due to colchicine. His medical history included chronic lymphocytic leukemia (CLL), pseudogout, osteoarthritis, and hypertension. In February 2011, his white blood cell (WBC) count was 2700 cells/μL, and his absolute neutrophil count (ANC) was 2200 cells/μL. Colchicine 0.6 mg orally daily was initiated in March for the prophylaxis of pseudogout. His WBC count decreased, and his colchicine dosage was reduced to 0.6 mg every other day. Despite this decreased dosage, his WBC count and ANC were 600 and 100 cells/μL, respectively, in September. In October, the patient received chemotherapy for presumed worsening of his CLL. One month later, his WBC count and ANC were 400 and 200 cells/μL, respectively. Subcutaneous filgrastim was administered, and colchicine was discontinued. At the end of November, he received another cycle of chemotherapy followed by pegfilgrastim. On the day of pegfilgrastim administration, the patient\u27s WBC count and ANC were 2000 and 1300 cells/μL, respectively. Two weeks later, his WBC count was 8800 cells/μL, and his ANC was 8300 cells/μL. Daily colchicine was restarted at the end of December. Two months later, his WBC count and ANC were 800 and 500 cells/μL, respectively. Given the symptomatic relief with colchicine, therapy was continued with close monitoring. Conclusion A patient with CLL developed leukopenia in association with colchicine administration for pseudogout

Brr2p-mediated conformational rearrangements in the spliceosome during activation and substrate repositioning

Brr2p is one of eight RNA helicases involved in pre-mRNA splicing. Detailed understanding of the functions of Brr2p and other spliceosomal helicases has been limited by lack of knowledge of their in vivo substrates. To address this, sites of direct Brr2p–RNA interaction were identified by in vivo UV cross-linking in budding yeast. Cross-links identified in the U4 and U6 small nuclear RNAs (snRNAs) suggest U4/U6 stem I as a Brr2p substrate during spliceosome activation. Further Brr2p cross-links were identified in loop 1 of the U5 snRNA and near splice sites and 3′ ends of introns, suggesting the possibility of a previously uncharacterized function for Brr2p in the catalytic center of the spliceosome. Consistent with this, mutant brr2-G858R reduced second-step splicing efficiency and enhanced cross-linking to 3′ ends of introns. Furthermore, RNA sequencing indicated preferential inhibition of splicing of introns with structured 3′ ends. The Brr2-G858Rp cross-linking pattern in U6 was consistent with an open conformation for the catalytic center of the spliceosome during first-to-second-step transition. We propose a previously unsuspected function for Brr2p in driving conformational rearrangements that lead to competence for the second step of splicing

Finite difference time domain modeling of steady state scattering from jet engines with moving turbine blades

The approach chosen to model steady state scattering from jet engines with moving turbine blades is based upon the Finite Difference Time Domain (FDTD) method. The FDTD method is a numerical electromagnetic program based upon the direct solution in the time domain of Maxwell's time dependent curl equations throughout a volume. One of the strengths of this method is the ability to model objects with complicated shape and/or material composition. General time domain functions may be used as source excitations. For example, a plane wave excitation may be specified as a pulse containing many frequencies and at any incidence angle to the scatterer. A best fit to the scatterer is accomplished using cubical cells in the standard cartesian implementation of the FDTD method. The material composition of the scatterer is determined by specifying its electrical properties at each cell on the scatterer. Thus, the FDTD method is a suitable choice for problems with complex geometries evaluated at multiple frequencies. It is assumed that the reader is familiar with the FDTD method

Event-driven simulations of a plastic, spiking neural network

We consider a fully-connected network of leaky integrate-and-fire neurons with spike-timing-dependent plasticity. The plasticity is controlled by a parameter representing the expected weight of a synapse between neurons that are firing randomly with the same mean frequency. For low values of the plasticity parameter, the activities of the system are dominated by noise, while large values of the plasticity parameter lead to self-sustaining activity in the network. We perform event-driven simulations on finite-size networks with up to 128 neurons to find the stationary synaptic weight conformations for different values of the plasticity parameter. In both the low and high activity regimes, the synaptic weights are narrowly distributed around the plasticity parameter value consistent with the predictions of mean-field theory. However, the distribution broadens in the transition region between the two regimes, representing emergent network structures. Using a pseudophysical approach for visualization, we show that the emergent structures are of "path" or "hub" type, observed at different values of the plasticity parameter in the transition region.Comment: 9 pages, 6 figure

Hairiness: the missing link between pollinators and pollination

Background. Functional traits are the primary biotic component driving organism influence on ecosystem functions; in consequence, traits are widely used in ecological research. However, most animal trait-based studies use easy-to-measure characteristics of species that are at best only weakly associated with functions. Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power. Methods. Here, we show that a simple, easy to measure trait (hairiness) can predict pollinator effectiveness with high accuracy. We used a novel image analysis method to calculate entropy values for insect body surfaces as a measure of hairiness. We evaluated the power of our method for predicting pollinator effectiveness by regressing pollinator hairiness (entropy) against single visit pollen deposition (SVD) and pollen loads on insects. We used linear models and AICC model selection to determine which body regions were the best predictors of SVD and pollen load. Results. We found that hairiness can be used as a robust proxy of SVD. The best models for predicting SVD for the flower species Brassica rapa and Actinidia deliciosa were hairiness on the face and thorax as predictors (R2 D0:98 and 0.91 respectively). The best model for predicting pollen load for B. rapa was hairiness on the face (R2 D0:81). Discussion. We suggest that the match between pollinator body region hairiness and plant reproductive structure morphology is a powerful predictor of pollinator effectiveness. We show that pollinator hairiness is strongly linked to pollination an important ecosystem function, and provide a rigorous and time-efficient method for measuring hairiness. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide.University of Auckland PCIG14-GA- 2013-631653, MBIE C11X130

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification