Stable U(IV) Complexes Form at High-Affinity Mineral Surface Sites

Uranium (U) poses a significant contamination hazard to soils, sediments, and groundwater due to its extensive use for energy production. Despite advances in modeling the risks of this toxic and radioactive element, lack of information about the mechanisms controlling U transport hinders further improvements, particularly in reducing environments where UIV predominates. Here we establish that mineral surfaces can stabilize the majority of U as adsorbed UIV species following reduction of UVI. Using X-ray absorption spectroscopy and electron imaging analysis, we find that at low surface loading, UIV forms inner-sphere complexes with two metal oxides, TiO2 (rutile) and Fe3O4 (magnetite) (at <1.3 U nm–2 and <0.037 U nm–2, respectively). The uraninite (UO2) form of UIV predominates only at higher surface loading. UIV–TiO2 complexes remain stable for at least 12 months, and UIV–Fe3O4 complexes remain stable for at least 4 months, under anoxic conditions. Adsorbed UIV results from UVI reduction by FeII or by the reduced electron shuttle AH2QDS, suggesting that both abiotic and biotic reduction pathways can produce stable UIV–mineral complexes in the subsurface. The observed control of high-affinity mineral surface sites on UIV speciation helps explain the presence of nonuraninite UIV in sediments and has important implications for U transport modeling

Mycobacterium tuberculosis Glucosyl-3-Phosphoglycerate Synthase: Structure of a Key Enzyme in Methylglucose Lipopolysaccharide Biosynthesis

Tuberculosis constitutes today a serious threat to human health worldwide, aggravated by the increasing number of identified multi-resistant strains of Mycobacterium tuberculosis, its causative agent, as well as by the lack of development of novel mycobactericidal compounds for the last few decades. The increased resilience of this pathogen is due, to a great extent, to its complex, polysaccharide-rich, and unusually impermeable cell wall. The synthesis of this essential structure is still poorly understood despite the fact that enzymes involved in glycosidic bond synthesis represent more than 1% of all M. tuberculosis ORFs identified to date. One of them is GpgS, a retaining glycosyltransferase (GT) with low sequence homology to any other GTs of known structure, which has been identified in two species of mycobacteria and shown to be essential for the survival of M. tuberculosis. To further understand the biochemical properties of M. tuberculosis GpgS, we determined the three-dimensional structure of the apo enzyme, as well as of its ternary complex with UDP and 3-phosphoglycerate, by X-ray crystallography, to a resolution of 2.5 and 2.7 Å, respectively. GpgS, the first enzyme from the newly established GT-81 family to be structurally characterized, displays a dimeric architecture with an overall fold similar to that of other GT-A-type glycosyltransferases. These three-dimensional structures provide a molecular explanation for the enzyme's preference for UDP-containing donor substrates, as well as for its glucose versus mannose discrimination, and uncover the structural determinants for acceptor substrate selectivity. Glycosyltransferases constitute a growing family of enzymes for which structural and mechanistic data urges. The three-dimensional structures of M. tuberculosis GpgS now determined provide such data for a novel enzyme family, clearly establishing the molecular determinants for substrate recognition and catalysis, while providing an experimental scaffold for the structure-based rational design of specific inhibitors, which lay the foundation for the development of novel anti-tuberculosis therapies

Cokriging for multivariate Hilbert space valued random fields: application to multi-fidelity computer code emulation

In this paper we propose Universal trace co-kriging, a novel methodology for interpolation of multivariate Hilbert space valued functional data. Such data commonly arises in multi-fidelity numerical modeling of the subsurface and it is a part of many modern uncertainty quantification studies. Besides theoretical developments we also present methodological evaluation and comparisons with the recently published projection based approach by Bohorquez et al. (Stoch Environ Res Risk Assess 31(1):53–70, 2016. https://doi.org/10.1007/s00477-016-1266-y). Our evaluations and analyses were performed on synthetic (oil reservoir) and real field (uranium contamination) subsurface uncertainty quantification case studies. Monte Carlo analyses were conducted to draw important conclusions and to provide practical guidelines for all future practitioners