Architecturally diverse proteins converge on an analogous mechanism to inactivate Uracil-DNA glycosylase

Uracil-DNA glycosylase (UDG) compromises the replication strategies of diverse viruses from unrelated lineages. Virally encoded proteins therefore exist to limit, inhibit or target UDG activity for proteolysis. Viral proteins targeting UDG, such as the bacteriophage proteins ugi, and p56, and the HIV-1 protein Vpr, share no sequence similarity, and are not structurally homologous. Such diversity has hindered identification of known or expected UDG-inhibitory activities in other genomes. The structural basis for UDG inhibition by ugi is well characterized; yet, paradoxically, the structure of the unbound p56 protein is enigmatically unrevealing of its mechanism. To resolve this conundrum, we determined the structure of a p56 dimer bound to UDG. A helix from one of the subunits of p56 occupies the UDG DNA-binding cleft, whereas the dimer interface forms a hydrophobic box to trap a mechanistically important UDG residue. Surprisingly, these p56 inhibitory elements are unexpectedly analogous to features used by ugi despite profound architectural disparity. Contacts from B-DNA to UDG are mimicked by residues of the p56 helix, echoing the role of ugi’s inhibitory beta strand. Using mutagenesis, we propose that DNA mimicry by p56 is a targeting and specificity mechanism supporting tight inhibition via hydrophobic sequestration

Screening and quantification of micro(nano)plastics and plastic additives in the seawater of Mar Menor lagoon

In this work a suspect-screening approach was employed to assess the polymers and plastic additives of micro(nano)plastics (NPL/MPLs) of size ranges from the nm range to 20 μm present in seawater from the top 5 cm of the Mar Menor lagoon during two sampling campaigns (summer and winter), as well of other potentially adsorbed compounds onto the plastic particles surfaces and suspended material. The identification of NPL/MPLs has been based on characteristic Kendrick Mass Defect analysis for each polymer type in mass spectra. The applied methodology allowed to identify NPLs/MPLs of polystyrene (PS), polyethylene (PE), polyisoprene (PI), polybutadiene (PBD), polypropylene (PP), polyamides (PA), polyvinylchloride (PVC), n-isopropylacrylamide (PNIPAm), and polydimethylsiloxanes. In addition, PS, PE, PI, PBD, PP, PA, and PVC were confirmed with standards, and the equivalent concentrations were quantified. The results of this study showed that most frequently found compounds were PP, PE, PA and PNIPAm, while the compound found at higher concentrations was by far PP reaching the 9,303 ± 366 ng/mL in one of the samples. A total number of 135 chemical compounds were tentatively identified, 74 of them plastic additives and compounds used in the polymers manufacture or coming from the polymer’s decomposition. In relation to plastic additives, the more frequently tentatively identified compounds were plasticizers such as phthalates group; stabilizers such as antioxidants (e.g., distearyl 3,3′-thiodipropionate, 2,5-di-tert-butylhydroquinone), and UV filters as benzotriazoles. Several flame retardants of the group of phosphates were as well detected. The other compounds tentatively identified in the samples were pharmaceuticals, pesticides, food additives, flavors and natural products that were attached onto the plastic particles and particulate matter from surrounding waters. In regards to the seasonal variation, during the summer a major number of compounds were tentatively detected, while de concentrations of polymers were slightly higher in winter. The spatial distribution showed higher contamination in the southern part of the coastal lagoon.Postprin

COL4A5 and LAMA5 variants co-inherited in familial hematuria: Digenic inheritance or genetic modifier effect?

Background: About 40-50% of patients with familial microscopic hematuria (FMH) caused by thin basement membrane nephropathy (TBMN) inherit heterozygous mutations in collagen IV genes (COL4A3, COL4A4). On long follow-up, the full phenotypic spectrum of these patients varies a lot, ranging from isolated MH or MH plus low-grade proteinuria to chronic renal failure of variable degree, including end-stage renal disease (ESRD). Methods: Here, we performed Whole Exome Sequencing (WES) in patients of six families, presenting with autosomal dominant FMH, with or without progression to proteinuria and loss of renal function, all previously found negative for severe collagen IV mutations. Hierarchical filtering of the WES data was performed, followed by mutation prediction analysis, Sanger sequencing and genetic segregation analysis. Results: In one family with four patients, we found evidence for the contribution of two co-inherited variants in two crucial genes expressed in the glomerular basement membrane (GBM); LAMA5-p.Pro1243Leu and COL4A5-p.Asp654Tyr. Mutations in COL4A5 cause classical X-linked Alport Syndrome, while rare mutations in the LAMA5 have been reported in patients with focal segmental glomerulosclerosis. The phenotypic spectrum of the patients includes hematuria, proteinuria, focal segmental glomerulosclerosis, loss of kidney function and renal cortical cysts. Conclusions: A modifier role of LAMA5 on the background of a hypomorphic Alport syndrome causing mutation is a possible explanation of our findings. Digenic inheritance is another scenario, following the concept that mutations at both loci more accurately explain the spectrum of symptoms, but further investigation is needed under this concept. This is the third report linking a LAMA5 variant with human renal disease and expanding the spectrum of genes involved in glomerular pathologies accompanied by familial hematurias. The cystic phenotype overlaps with that of a mouse model, which carried a Lama5 hypomorphic mutation that caused severely reduced Lama5 protein levels and produced kidney cysts. 2018 The Author(s).The work was supported from the Cyprus Research Promotion Foundation through the grant NEW INFRASTRUCTURE/STRATEGIC/0308/24 to CD (co-funded by the European Regional Development Fund and the Republic of Cyprus). The funding body did not contribute to the design of study, collection, analysis and interpretation of data, or in manuscript writing.Scopu

GeoTriples: Transforming geospatial data into RDF graphs using R2RML and RML mappings

A lot of geospatial data has become available at no charge in many countries recently. Geospatial data that is currently made available by government agencies usually do not follow the linked data paradigm. In the few cases where government agencies do follow the linked data paradigm (e.g., Ordnance Survey in the United Kingdom), specialized scripts have been used for transforming geospatial data into RDF. In this paper we present the open source tool GeoTriples which generates and processes extended R2RML and RML mappings that transform geospatial data from many input formats into RDF. GeoTriples allows the transformation of geospatial data stored in raw files (shapefiles, CSV, KML, XML, GML and GeoJSON) and spatially-enabled RDBMS (PostGIS and MonetDB) into RDF graphs using well-known vocabularies like GeoSPARQL and stSPARQL, but without being tightly coupled to a specific vocabulary. GeoTriples has been developed in European projects LEO and Melodies and has been used to transform many geospatial data sources into linked data. We study the performance of GeoTriples experimentally using large publicly available geospatial datasets, and show that GeoTriples is very efficient and scalable especially when its mapping processor is implemented using Apache Hadoop

Generalized dynamical density functional theory for classical fluids and the significance of inertia and hydrodynamic interactions

We study the dynamics of a colloidal fluid including inertia and hydrodynamic interactions, two effects which strongly influence the non-equilibrium properties of the system. We derive a general dynamical density functional theory (DDFT) which shows very good agreement with full Langevin dynamics. In suitable limits, we recover existing DDFTs and a Navier-Stokes-like equation with additional non-local terms.Comment: 5 pages, 4 figures, 4 supplementary movie files, I supplementary pd

Unification of dynamic density functional theory for colloidal fluids to include inertia and hydrodynamic interactions: derivation and numerical experiments.

Starting from the Kramers equation for the phase-space dynamics of the N-body probability distribution, we derive a dynamical density functional theory (DDFT) for colloidal fluids including the effects of inertia and hydrodynamic interactions (HI). We compare the resulting theory to extensive Langevin dynamics simulations for both hard rod systems and three-dimensional hard sphere systems with radially symmetric external potentials. As well as demonstrating the accuracy of the new DDFT, by comparing with previous DDFTs which neglect inertia, HI, or both, we also scrutinize the significance of including these effects. Close to local equilibrium we derive a continuum equation from the microscopic dynamics which is a generalized Navier–Stokes-like equation with additional non-local terms governing the effects of HI. For the overdamped limit we recover analogues of existing configuration-space DDFTs but with a novel diffusion tensor

GRAB: A Dataset of Whole-Body Human Grasping of Objects

Training computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, detailed contact information, hand pose and shape, and the 3D body motion over time. While "grasping" is commonly thought of as a single hand stably lifting an object, we capture the motion of the entire body and adopt the generalized notion of "whole-body grasps". Thus, we collect a new dataset, called GRAB (GRasping Actions with Bodies), of whole-body grasps, containing full 3D shape and pose sequences of 10 subjects interacting with 51 everyday objects of varying shape and size. Given MoCap markers, we fit the full 3D body shape and pose, including the articulated face and hands, as well as the 3D object pose. This gives detailed 3D meshes over time, from which we compute contact between the body and object. This is a unique dataset, that goes well beyond existing ones for modeling and understanding how humans grasp and manipulate objects, how their full body is involved, and how interaction varies with the task. We illustrate the practical value of GRAB with an example application; we train GrabNet, a conditional generative network, to predict 3D hand grasps for unseen 3D object shapes. The dataset and code are available for research purposes at https://grab.is.tue.mpg.de.Comment: ECCV 202