Nature's recipe: A theoretical study analyzes how the environment of the [FeFe] hydrogenase's catalytic cofactor affects its chemical properties, particularly the relative stability of complexes with bridging and terminal hydride ligands (see picture; Fe teal, S yellow, C green, N blue, O red, H gray). The results help to elucidate key rules for the design of bioinspired synthetic catalysts for H(2) production.

Catalytic metal sites in enzymes frequently have second-sphere carboxylate groups that neutralize the charge of the site and share protons with first-sphere ligands. This gives rise to an ambiguity concerning the position of this proton, which has turned out to be hard to settle with experimental, as well as theoretical, methods. We study three such proton-transfer reactions in two proteins and show that, in [Ni,Fe] hydrogenase, the bridging Cys-546 ligand is deprotonated by His-79, whereas in oxidized copper nitrite reductase, the His-100 ligand is neutral and the copper-bound water molecule is deprotonated by Asp-98. We show that these reactions strongly depend on the electrostatic interactions with the surrounding protein and solvent, because there is a large change in the dipole moment of the active site (2-6 D). Neither vacuum quantum mechanical (QM) calculations with large models, a continuum solvent, or a Poisson-Boltzmann treatment of the surroundings, nor combined QM and molecular mechanics (QM/MM) optimizations give reliable estimates of the proton-transfer energies (mean absolute deviations of over 20 kJ/mol). Instead, QM/MM free-energy perturbations are needed to obtain reliable estimates of the reaction energies. These calculations also indicate what interactions and residues are important for the energy, showing how the quantum system may be systematically enlarged. With such a procedure, results with an uncertainty of ∼10 kJ/mol can be obtained, provided that a proper QM method is used.

SummaryX-ray photoelectron spectroscopy (XPS) is a widely used tool for studying the chemical composition of materials and it is a standard technique in surface science and technology. XPS is particularly useful for characterizing nanostructures such as carbon nanomaterials due to their reduced dimensionality. In order to assign the measured binding energies to specific bonding environments, reference energy values need to be known. Experimental measurements of the core level signals of the elements present in novel materials such as graphene have often been compared to values measured for molecules, or calculated for finite clusters. Here we have calculated core level binding energies for variously functionalized or defected graphene by delta Kohn–Sham total energy differences in the real-space grid-based projector-augmented wave density functional theory code (GPAW). To accurately model extended systems, we applied periodic boundary conditions in large unit cells to avoid computational artifacts. In select cases, we compared the results to all-electron calculations using an ab initio molecular simulations (FHI-aims) code. We calculated the carbon and oxygen 1s core level binding energies for oxygen and hydrogen functionalities such as graphane-like hydrogenation, and epoxide, hydroxide and carboxylic functional groups. In all cases, we considered binding energy contributions arising from carbon atoms up to the third nearest neighbor from the functional group, and plotted C 1s line shapes by using experimentally realistic broadenings. Furthermore, we simulated the simplest atomic defects, namely single and double vacancies and the Stone–Thrower–Wales defect. Finally, we studied modifications of a reactive single vacancy with O and H functionalities, and compared the calculated values to data found in the literature.

Knowledge on the genetic epidemiology of disorders in the dog population has implications for both veterinary medicine and sustainable breeding. Limited data on frequencies of genetic disease variants across breeds exists, and the disease heritage of mixed breed dogs remains poorly explored to date. Advances in genetic screening technologies now enable comprehensive investigations of the canine disease heritage, and generate health-related big data that can be turned into action. We pursued population screening of genetic variants implicated in Mendelian disorders in the largest canine study sample examined to date by examining over 83,000 mixed breed and 18,000 purebred dogs representing 330 breeds for 152 known variants using a custom-designed beadchip microarray. We further announce the creation of MyBreedData (www.mybreeddata.com), an online updated inherited disorder prevalence resource with its foundation in the generated data. We identified the most prevalent, and rare, disease susceptibility variants across the general dog population while providing the first extensive snapshot of the mixed breed disease heritage. Approximately two in five dogs carried at least one copy of a tested disease variant. Most disease variants are shared by both mixed breeds and purebreds, while breed- or line-specificity of others is strongly suggested. Mixed breed dogs were more likely to carry a common recessive disease, whereas purebreds were more likely to be genetically affected with one, providing DNA-based evidence for hybrid vigor. We discovered genetic presence of 22 disease variants in at least one additional breed in which they were previously undescribed. Some mutations likely manifest similarly independently of breed background; however, we emphasize the need for follow up investigations in each case and provide a suggested validation protocol for broader consideration. In conclusion, our study provides unique insight into genetic epidemiology of canine disease risk variants, and their relevance for veterinary medicine, breeding programs and animal welfare.

SignificanceUrban, Westernized populations suffer extensively from noncommunicable diseases such as allergies. However, the overlapping effects of living environment and lifestyle are difficult to separate. Intriguingly, also our fellow animals, dogs, suffer from analogous diseases. Therefore, we suggest that pet dogs, sharing their environment and lifestyle with humans but having a comparatively simple life, provide a valuable model for understanding origins of noncommunicable diseases. We show that living environment and lifestyle concurrently, but still independently, shape both the skin microbiota and the risk of allergic disease in dogs. Urbanized lifestyle, featuring restricted animal contacts and small family size, is allergy promoting both in rural and urban dogs. Hence, both environment and lifestyle seem to influence the microbiota and, probably consequently, immune tolerance.

We used two theoretical methods to estimate reduction potentials and acidity constants in Mn superoxide dismutase (MnSOD), namely combined quantum mechanical and molecular mechanics (QM/MM) thermodynamic cycle perturbation (QTCP) and the QM/MM-PBSA approach. In the latter, QM/MM energies are combined with continuum solvation energies calculated by solving the Poisson-Boltzmann equation (PB) or by the generalised Born approach (GB) and non-polar solvation energies calculated from the solvent-exposed surface area. We show that using the QTCP method, we can obtain accurate and precise estimates of the proton-coupled reduction potential for MnSOD, 0.30±0.01 V, which compares favourably with experimental estimates of 0.26-0.40 V. However, the calculated potentials depend strongly on the DFT functional used: The B3LYP functional gives 0.6 V more positive potentials than the PBE functional. The QM/MM-PBSA approach leads to somewhat too high reduction potentials for the coupled reaction and the results depend on the solvation model used. For reactions involving a change in the net charge of the metal site, the corresponding results differ by up to 1.3 V or 24 pK(a) units, rendering the QM/MM-PBSA method useless to determine absolute potentials. However, it may still be useful to estimate relative shifts, although the QTCP method is expected to be more accurate.

BackgroundThe growing number of identified genetic disease risk variants across dog breeds challenges the current state-of-the-art of population screening, veterinary molecular diagnostics, and genetic counseling. Multiplex screening of such variants is now technologically feasible, but its practical potential as a supportive tool for canine breeding, disease diagnostics, pet care, and genetics research is still unexplored.ResultsTo demonstrate the utility of comprehensive genetic panel screening, we tested nearly 7000 dogs representing around 230 breeds for 93 disease-associated variants using a custom-designed genotyping microarray (the MyDogDNA® panel test). In addition to known breed disease-associated mutations, we discovered 15 risk variants in a total of 34 breeds in which their presence was previously undocumented. We followed up on seven of these genetic findings to demonstrate their clinical relevance. We report additional breeds harboring variants causing factor VII deficiency, hyperuricosuria, lens luxation, von Willebrand’s disease, multifocal retinopathy, multidrug resistance, and rod-cone dysplasia. Moreover, we provide plausible molecular explanations for chondrodysplasia in the Chinook, cerebellar ataxia in the Norrbottenspitz, and familiar nephropathy in the Welsh Springer Spaniel.ConclusionsThese practical examples illustrate how genetic panel screening represents a comprehensive, efficient and powerful diagnostic and research discovery tool with a range of applications in veterinary care, disease research, and breeding. We conclude that several known disease alleles are more widespread across different breeds than previously recognized. However, careful follow up studies of any unexpected discoveries are essential to establish genotype-phenotype correlations, as is readiness to provide genetic counseling on their implications for the dog and its breed.

Because of its high specific surface area and unique electronic properties, graphene with substitutional impurity metal atoms and clusters attached to defects in the graphene sheet is attractive for use in hydrogen fuel cells for oxygen reduction at the cathode. In an attempt to find a cheap yet efficient catalyst for the reaction, we use density-functional theory calculations to study the structure and properties of transition-metal-vacancy complexes in graphene. We calculate formation energies of the complexes, which are directly related to their stability, along with oxygen and water adsorption energies. In addition to metals, we also consider nonmetal impurities like B, P, and Si, which form strong bonds with under-coordinated carbon atoms at defects in graphene. Our results indicate that single Ni, Pd, Pt, Sn, and P atoms embedded into divacancies in graphene are promising candidates for the use in fuel cell cathodes for oxygen reduction reaction (ORR). We further discuss how ion irradiation of graphene combined with metal sputtering and codeposition can be used to make an efficient and relatively inexpensive graphene-based material for hydrogen fuel cells.