Nocardioides nematodiphilus sp. nov., isolated from rhizosphere of Arabidopsis thaliana.

An actinobacterial strain, designated R-N-C8T, was isolated from the rhizosphere soil of Arabidopsis thaliana collected in Yunnan Province, south-west China. Based on the results of 16S rRNA gene sequence analysis, strain R-N-C8T had highest similarity to Nocardioides terrae CGMCC 1.7056T (96.5%), Nocardioides opuntiae KCTC 19804T (96.3%) and Nocardioides currus IB-3T (96.1%), and lower than 96.0 % similarity to other members of the genus Nocardioides. Phylogenetic trees based on 16S rRNA gene sequences indicated that strain R-N-C8T formed an isolated branch with N. terrae CGMCC 1.7056T and N. opuntiae KCTC 19804T. The polar lipids contained phosphatidylglycerol, diphosphatidylglycerol, one unidentified phosphoglycolipid and four unidentified phospholipids in the cellular membrane. The major fatty acids were identified as iso-C16 : 0, anteiso-C17 : 0, iso-C17 : 0, summed feature 9 (iso-C17 : 1 ω9c and/or C16 : 0 10-methyl) and iso-C15 : 0. The predominant respiratory quinone was MK-8(H4) and ll-diaminopimelic acid was the diagnostic diamino acid in the cell-wall peptidoglycan. The genomic DNA G+C content was 70.9 mol%. The orthologous average nucleotide identiy values between N. terrae CGMCC 1.7056T, N. currus IB-3T and strain R-N-C8T were 77.1 and 75.1 %, respectively. DNA-DNA hybridization values between N. terrae CGMCC 1.7056T, N. currus IB-3T and strain R-N-C8T were 20.7 and 19.9 % respectively. Data from phenotypic and genotypic analyses supported that strain R-N-C8T represents a new species of Nocardioides, for which the name Nocardioides nematodiphilus sp. nov. is proposed. The type strain is R-N-C8T (=CGMCC 1.18723T= KCTC 49528T).

Characterizing the potentially neuronal acetylcholinesterase reactivity toward chiral pyraclofos: Enantioselective insights from spectroscopy, in silico docking, molecular dynamics simulation and per-residue energy decomposition studies.

Chiral organophosphorus agents are distributed ubiquitously in the environment, but the neuroactivity of these asymmetric chemicals to humans remains uncertain. This scenario was to explore the stereoselective neurobiological response of human acetylcholinesterase (AChE) to chiral pyraclofos at the enantiomeric scale, and then decipher the microscopic basis of enantioselective neurotoxicity of pyraclofos enantiomers. The results indicated that (R)-/(S)-pyraclofos can form the bioconjugates with AChE with a stoichiometric ratio of 1:1, but the neuronal affinity of (R)-pyraclofos (K = 6.31 × 104 M-1) with AChE was larger than that of (S)-pyraclofos (K = 1.86 × 104 M-1), and significant enantioselectivity was existed in the biochemical reaction. The modes of neurobiological action revealed that pyraclofos enantiomers were situated at the substrate binding domain, and the strength of the overall noncovalent bonds between (S)-pyraclofos and the residues was weaker than that of (R)-pyraclofos, resulting in the high inhibitory effect of (R)-pyraclofos toward the activity of AChE. Dynamic enantioselective biointeractions illustrated that the intervention of inherent conformational flexibility in the AChE-(R)-pyraclofos was greater than that of the AChE-(S)-pyraclofos, which arises from the big spatial displacement and the conformational flip of the binding domain composed of the residues Thr-64～Asn-89, Gly-122～Asp-134, and Thr-436～Tyr-449. Energy decomposition exhibited that the Gibbs free energies of the AChE-(R)-/(S)-pyraclofos were ΔG° = ï¼37.4/－30.2 kJ mol-1, respectively, and the disparity comes from the electrostatic energy during the stereoselective neurochemical reactions. Quantitative conformational analysis further confirmed the atomic-scale computational chemistry conclusions, and the perturbation of (S)-pyraclofos on the AChE's ordered conformation was lower than that of (R)-pyraclofos, which is germane to the interaction energies of the crucial residues, e.g. Tyr-124, Tyr-337, Asp-74, Trp-86, and Tyr-119. Evidently, this attempt will contribute mechanistic information to uncovering the neurobiological effects of chiral organophosphates on the body.

Effects of organic acids on the chemotaxis profiles and biocontrol traits of antagonistic bacterial endophytes against root-rot disease in Panax notoginseng.

Understanding the role of chemotaxis in ecological interactions between plants and microbes in the rhizosphere is necessary to optimize biocontrol strategies targeting plant soil-borne diseases. Therefore, we examined and profiled the antagonistic endophytic bacteria (AEB) population with chemotaxis potential in the medicinal plant Panax notoginseng using a cheA gene-based approach coupled with 16S rRNA sequencing. Phylogenetic analysis of the chemotactic AEB (CAEB) community in P. notoginseng enabled the identification of 56 CAEB strains affiliated with 30 species of Actinobacteria, Firmicutes, and Proteobacteria; Firmicutes, especially Bacillus, were predominant. We then systematically quantified the chemotactic response profiles of CAEB toward five organic acid (OA) attractants: citric acid, fumaric acid (FA), malic acid, oxalic acid, and succinic acid. Further hierarchical cluster analysis revealed that the chemotaxis of CAEB to the same attractant exhibited different patterns among not only genera but also species and even strains of the same species. Following chemotaxis and hierarchical analysis, we selected the strongest chemoattractant, fumaric acid (FA), as the target for evaluating the effects of OAs on the representative CAEB strain Bacillus amyloliquefaciens subsp. plantarum YP1. Application of FA significantly stimulated the chemotaxis ability and growth of YP1, and increased the transcript levels of cheA and biocontrol-related genes in YP1. This is the first study to characterise the diversity of chemotaxis profiles toward OAs in natural bacterial assemblages of P. notoginseng and to highlight how FA promotes the biocontrol-related traits of P. notoginseng-associated CAEB.

Theoretical study on the reaction mechanism and selectivity of acetylene semi-hydrogenation on Ni-Sn intermetallic catalysts.

Recently, Ni-Sn intermetallic compounds (IMCs) with unique geometric structures have been proved to be selective catalysts for acetylene hydrogenation to ethylene, but the origin of the selectivity remains unclear. In this work, a density functional theory (DFT) study has been carried out to investigate the mechanism of acetylene hydrogenation on six surfaces of Ni-Sn IMCs, and the geometric effects towards ethylene selectivity were revealed. Two key parameters (adsorption energy and the hydrogenation barrier of ethylene), which determine the ethylene selectivity, were studied quantitatively. The adsorption sites for C2Hy (y = 2, 3, 4) can be classified into three types: Type 1 (Ni3Sn(111) and Ni3Sn2(101)-2) with Ni trimers, Type 2 (Ni3Sn(001) and Ni3Sn2(001)) with Ni monomers, and Type 3 (Ni3Sn2(101) and Ni3Sn2(001)-2) with reconstructed metal trimers. The adsorption energy (Ead) decreases following the order: Type 1 > Type 3 > Type 2, which indicates that the adsorption strength depends significantly on site ensemble: a more isolated Ni site would facilitate the desorption of ethylene. However, the surface roughness mainly dominates the hydrogenation barrier of ethylene. Either low or high roughness decreases the interactions between H and C2H4 (Eint), resulting in an enhanced energy barrier for over-hydrogenation of C2H4 (Ea,hydr); while moderate roughness benefits Eint and lowers Ea,hydr. The selectivity to ethylene is denoted as ΔEa = Ea,hydr - |Ead|, thus depending on the interplay of site ensemble effects and surface roughness. From this point of view, Ni3Sn(001) and Ni3Sn2(101) surfaces with well-isolated Ni ensembles and low (or high) surface roughness exhibit decreased |Ead| and increased Ea,hydr, giving rise to excellent selectivity to ethylene. This work provides significant understanding of the origin of ethylene selectivity in terms of geometric effects, which gives helpful instruction for the design and preparation of intermetallic catalysts for acetylene semi-hydrogenation.

Effect of Annealing Temperature on the Water Contact Angle of PVD Hard Coatings.

Various PVD (physical vapor deposition) hard coatings including nitrides and metal-doped diamond-like carbons (Me-DLC) were applied in plastic injection and die-casting molds to improve wear resistance and reduce sticking. In this study, nitrides hcp-AlN (hexagonal close-packed AlN), Cr2N, (CrAl)2N) and Me-DLC (Si-DLC and Cr-DLC) coatings were prepared using a closed field unbalanced magnetron reactive sputtering system. The coatings were annealed in air for 2 h at various temperatures, after which the anti-sticking properties were assessed using water contact angle (WCA) measurements. The as-deposited hcp-AlN, Cr2N and (CrAl)2N coatings exhibit hydrophobic behavior and exhibit respective WCAs of 119°, 106° and 101°. The as-deposited Si-DLC and Cr-DLC coatings exhibit hydrophilic behavior and exhibit respective WCAs of 74° and 88°. The annealed Cr2N and (CrAl)2N coatings exhibit hydrophobic behavior with higher WCAs, while the annealed hcp-AlN, Si-DLC and Cr-DLC coatings are hydrophilic. The increased WCA of the annealed Cr2N and (CrAl)2N coatings is related to their crystal structure and increased roughness. The decreased WCA of the annealed hcp-AlN, Si-DLC and Cr-DLC coatings is related to their crystal structures and has little correlation with roughness.

Adaptive neuro-fuzzy approach for predicting hardness of deposited TiN/ZrN multilayer coatings.

This paper presents an adaptive neuro-fuzzy approach based on first order function of fuzzy model for establishing the relationship between control factors and thin films properties of TiN/ZrN coatings on Si(100) wafer substrates. A statistical model was designed to explore the space of the processes by an orthogonal array scheme. Eight control factors of closed unbalance magnetron sputtering system were selected for modeling the process, such as interlayer material, argon and nitrogen flow rate, titanium and zirconium target current, rotation speed, work distance, and bias voltage. Analysis of variance (ANOVA) was carried out for determining the influence of control factors. In this study, with the application of ANOVA, the smallest effect of control factors was eliminated. The adaptive neuro-fuzzy inference system (ANFIS) was applied as a tool to model the deposited process with five significant control factors. The experimental results show that ANFIS demonstrates better accuracy than additive model for the film hardness. The root mean square error between prediction values and experimental values were archived to 0.04.