Krüppel-associated box (KRAB)-associated co-repressor (KAP-1) Ser-473 phosphorylation regulates heterochromatin protein 1 (HP1- ) mobilization and DNA repair in heterochromatin

The DNA damage response encompasses a complex series of signaling pathways that function to regulate and facilitate the repair of damaged DNA. Recent studies have shown that the repair of transcriptionally inactive chromatin, named heterochromatin, is dependent upon the phosphorylation of the co-repressor, Krüppel-associated box (KRAB) domain-associated protein (KAP-1), by the ataxia telangiectasia-mutated (ATM) kinase. Co-repressors, such as KAP-1, function to regulate the rigid structure of heterochromatin by recruiting histone-modifying enzymes, such HDAC1/2, SETDB1, and nucleosome-remodeling complexes such as CHD3. Here, we have characterized a phosphorylation site in the HP1-binding domain of KAP-1, Ser-473, which is phosphorylated by the cell cycle checkpoint kinase Chk2. Expression of a nonphosphorylatable S473A mutant conferred cellular sensitivity to DNA-damaging agents and led to defective repair of DNA double-strand breaks in heterochromatin. In addition, cells expressing S473A also displayed defective mobilization of the HP1-β chromodomain protein. The DNA repair defect observed in cells expressing S473A was alleviated by depletion of HP1-β, suggesting that phosphorylation of KAP-1 on Ser-473 promotes the mobilization of HP1-β from heterochromatin and subsequent DNA repair. These results suggest a novel mechanism of KAP-1-mediated chromatin restructuring via Chk2-regulated HP1-β exchange from heterochromatin, promoting DNA repair.

Structure of the immature retroviral capsid at 8 Å resolution by cryo-electron microscopy

The assembly of retroviruses such as HIV-1 is driven by oligomerization of their major structural protein, Gag. Gag is a multidomain polyprotein including three conserved folded domains: MA (matrix), CA (capsid) and NC (nucleocapsid)(1). Assembly of an infectious virion proceeds in two stages(2). In the first stage, Gag oligomerization into a hexameric protein lattice leads to the formation of an incomplete, roughly spherical protein shell that buds through the plasma membrane of the infected cell to release an enveloped immature virus particle. In the second stage, cleavage of Gag by the viral protease leads to rearrangement of the particle interior, converting the non-infectious immature virus particle into a mature infectious virion. The immature Gag shell acts as the pivotal intermediate in assembly and is a potential target for anti-retroviral drugs both in inhibiting virus assembly and in disrupting virus maturation(3). However, detailed structural information on the immature Gag shell has not previously been available. For this reason it is unclear what protein conformations and interfaces mediate the interactions between domains and therefore the assembly of retrovirus particles, and what structural transitions are associated with retrovirus maturation. Here we solve the structure of the immature retroviral Gag shell from Mason-Pfizer monkey virus by combining cryo-electron microscopy and tomography. The 8-angstrom resolution structure permits the derivation of a pseudo-atomic model of CA in the immature retrovirus, which defines the protein interfaces mediating retrovirus assembly. We show that transition of an immature retrovirus into its mature infectious form involves marked rotations and translations of CA domains, that the roles of the amino-terminal and carboxy-terminal domains of CA in assembling the immature and mature hexameric lattices are exchanged, and that the CA interactions that stabilize the immature and mature viruses are almost completely distinct.

An ensemble method for predicting subnuclear localizations from primary protein structures

Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpr​ed_page.php.

Modified alumina nanofiber membranes for protein separation

Large-scale purification/separation of bio-substances is a key technology required for rapid production of biological substances in bioengineering. Membrane filtration is a new separation process and has potential to be used for concentration (removal of solvent), desalting (removal of low molecular weight compounds), clarification (removal of particles), and fractionation (protein-protein separation). In this study, we developed an efficient membrane for protein separation based on ceramic nanofibers. Alumina nanofibers were prepared on a porous support and formed large flow passages. The radical changes in membrane structure provided new ceramic membranes with a large porosity (more than 70%) due to the replacement of bulk particles with fine fibers as building components. The pore size had an average of 11 nm and pure water flux was approximately 360 L•h-1•m-2•bar-1. Further surface modification with a self-assembled monolayer of (3-aminopropyl) triethoxysilane enhanced the membrane filtration properties. Characterization with SEM, FTIR, contact angle, and proteins separation tests indicated that the fibril layers uniformly spread on the surface of the porous support. Moreover, the membrane surface was changed from hydrophilic to hydrophobic after silane groups were grafted. It demonstrated that the silane-grafted alumina fiber membrane can reject 100% BSA protein and 92% cellulase protein. It was also able to retain 75% trypsin protein while maintaining a permeation flux of 48 L•h-1•m-2•bar-1.

Analysis and prediction of the critical current density across [001]-tilt YBa2Cu3O7- grain boundaries of arbitrary misorientation angles

A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.

The structure of Pavlovian fear conditioning in the amygdala

Do different brains forming a specific memory allocate the same groups of neurons to encode it? One way to test this question is to map neurons encoding the same memory and quantitatively compare their locations across individual brains. In a previous study, we used this strategy to uncover a common topography of neurons in the dorsolateral amygdala (LAd) that expressed a learning-induced and plasticity-related kinase (p42/44 mitogen-activated protein kinase; pMAPK), following auditory Pavlovian fear conditioning. In this series of experiments, we extend our initial findings to ask to what extent this functional topography depends upon intrinsic neuronal structure. We first showed that the majority (87 %) of pMAPK expression in the lateral amygdala was restricted to principal-type neurons. Next, we verified a neuroanatomical reference point for amygdala alignment using in vivo magnetic resonance imaging and in vitro morphometrics. We then determined that the topography of neurons encoding auditory fear conditioning was not exclusively governed by principal neuron cytoarchitecture. These data suggest that functional patterning of neurons undergoing plasticity in the amygdala following Pavlovian fear conditioning is specific to memory formation itself. Further, the spatial allocation of activated neurons in the LAd was specific to cued (auditory), but not contextual, fear conditioning. Spatial analyses conducted at another coronal plane revealed another spatial map unique to fear conditioning, providing additional evidence that the functional topography of fear memory storing cells in the LAd is non-random and stable. Overall, these data provide evidence for a spatial organizing principle governing the functional allocation of fear memory in the amygdala.

The Arabidopsis thaliana double-stranded RNA binding protein DRB1 directs guide strand selection from microRNA duplexes

In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.

Small RNA sequencing of potato leafroll virus-infected plants reveals an additional subgenomic RNA encoding a sequence-specific RNA-binding protein

Potato leafroll virus (PLRV) is a positive-strand RNA virus that generates subgenomic RNAs (sgRNA) for expression of 3' proximal genes. Small RNA (sRNA) sequencing and mapping of the PLRV-derived sRNAs revealed coverage of the entire viral genome with the exception of four distinctive gaps. Remarkably, these gaps mapped to areas of PLRV genome with extensive secondary structures, such as the internal ribosome entry site and 5' transcriptional start site of sgRNA1 and sgRNA2. The last gap mapped to ~500. nt from the 3' terminus of PLRV genome and suggested the possible presence of an additional sgRNA for PLRV. Quantitative real-time PCR and northern blot analysis confirmed the expression of sgRNA3 and subsequent analyses placed its 5' transcriptional start site at position 5347 of PLRV genome. A regulatory role is proposed for the PLRV sgRNA3 as it encodes for an RNA-binding protein with specificity to the 5' of PLRV genomic RNA. © 2013.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Consensus σ70 promoter prediction using hadoop

MapReduce frameworks such as Hadoop are well suited to handling large sets of data which can be processed separately and independently, with canonical applications in information retrieval and sales record analysis. Rapid advances in sequencing technology have ensured an explosion in the availability of genomic data, with a consequent rise in the importance of large scale comparative genomics, often involving operations and data relationships which deviate from the classical Map Reduce structure. This work examines the application of Hadoop to patterns of this nature, using as our focus a wellestablished workflow for identifying promoters - binding sites for regulatory proteins - Across multiple gene regions and organisms, coupled with the unifying step of assembling these results into a consensus sequence. Our approach demonstrates the utility of Hadoop for problems of this nature, showing how the tyranny of the "dominant decomposition" can be at least partially overcome. It also demonstrates how load balance and the granularity of parallelism can be optimized by pre-processing that splits and reorganizes input files, allowing a wide range of related problems to be brought under the same computational umbrella.

Actinidia DRM1 : an intrinsically disordered protein whose mRNA expression is inversely correlated with spring budbreak in Kiwifruit

Intrinsically disordered proteins (IDPs) are a relatively recently defined class of proteins which, under native conditions, lack a unique tertiary structure whilst maintaining essential biological functions. Functional classification of IDPs have implicated such proteins as being involved in various physiological processes including transcription and translation regulation, signal transduction and protein modification. Actinidia DRM1 (Ade DORMANCY ASSOCIATED GENE 1), represents a robust dormancy marker whose mRNA transcript expression exhibits a strong inverse correlation with the onset of growth following periods of physiological dormancy. Bioinformatic analyses suggest that DRM1 is plant specific and highly conserved at both the nucleotide and protein levels. It is predicted to be an intrinsically disordered protein with two distinct highly conserved domains. Several Actinidia DRM1 homologues, which align into two distinct Actinidia-specific families, Type I and Type II, have been identified. No candidates for the Arabidopsis DRM1-Homologue (AtDRM2) an additional family member, has been identified in Actinidia.

Time to face the fats : What can mass spectrometry reveal about the structure of lipids and their interactions with proteins?

Since the 1950s, X-ray crystallography has been the mainstay of structural biology, providing detailed atomic-level structures that continue to revolutionize our understanding of protein function. From recent advances in this discipline, a picture has emerged of intimate and specific interactions between lipids and proteins that has driven renewed interest in the structure of lipids themselves and raised intriguing questions as to the specificity and stoichiometry in lipid-protein complexes. Herein we demonstrate some of the limitations of crystallography in resolving critical structural features of ligated lipids and thus determining how these motifs impact protein binding. As a consequence, mass spectrometry must play an important and complementary role in unraveling the complexities of lipid-protein interactions. We evaluate recent advances and highlight ongoing challenges towards the twin goals of (1) complete structure elucidation of low, abundant, and structurally diverse lipids by mass spectrometry alone, and (2) assignment of stoichiometry and specificity of lipid interactions within protein complexes.

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership.

Structure and assembly of immature HIV

The major structural components of HIV are synthesized as a 55-kDa polyprotein, Gag. Particle formation is driven by the self-assembly of Gag into a curved hexameric lattice, the structure of which is poorly understood. We used cryoelectron tomography and contrast-transfer-function corrected subtomogram averaging to study the structure of the assembled immature Gag lattice to approximate to 17-angstrom resolution. Gag is arranged in the immature virus as a single, continuous, but incomplete hexameric lattice whose curvature is mediated without a requirement for pentameric defects. The resolution of the structure allows positioning of individual protein domains. High-resolution crystal structures were fitted into the reconstruction to locate protein-protein interfaces involved in Gag assembly, and to identify the structural transformations associated with virus maturation. The results of this study suggest a concept for the formation of nonsymmetrical enveloped viruses of variable sizes.

The antigen 43 structure reveals a molecular velcro-like mechanism of autotransporter-mediated bacterial clumping

Aggregation and biofilm formation are critical mechanisms for bacterial resistance to host immune factors and antibiotics. Autotransporter (AT) proteins, which represent the largest group of outer-membrane and secreted proteins in Gram-negative bacteria, contribute significantly to these phenotypes. Despite their abundance and role in bacterial pathogenesis, most AT proteins have not been structurally characterized, and there is a paucity of detailed information with regard to their mode of action. Here we report the structure–function relationships of Antigen 43 (Ag43a), a prototypic self-associating AT protein from uropathogenic Escherichia coli. The functional domain of Ag43a displays a twisted L-shaped β-helical structure firmly stabilized by a 3D hydrogen-bonded scaffold. Notably, the distinctive Ag43a L shape facilitates self-association and cell aggregation. Combining all our data, we define a molecular “Velcro-like” mechanism of AT-mediated bacterial clumping, which can be tailored to fit different bacterial lifestyles such as the formation of biofilms.