Notes

Early on diagenesis of anthropogenic uranium throughout waters acquiring heavy groundwater through the Kiruna mine, north Norway.
Modulating photoswitch functionality with halogen, coordinative and also hydrogen binding: an assessment associated with family member bond advantages.
DNA extracted from fecal samples contains DNA from the focal species, food, bacteria and pathogens. Most DNA quantification methods measure total DNA and cannot differentiate among sources. Despite the desirability of noninvasive fecal sampling for studying wildlife populations, low amounts of focal species DNA make it difficult to use for next-generation sequencing (NGS), where accurate DNA quantification is critical for normalization. Two factors are required prior to using fecal samples in NGS libraries (1) an accurate quantification method for the amount of target DNA and (2) a determination of the relative amount of target DNA needed for successful single nucleotide polymorphism genotyping assays. Here, we address these needs by developing primers to amplify a 101 bp region of the nuclear F2 gene and a quantitative PCR (qPCR) assay that allows the accurate quantification of the amount of polar bear (Ursus maritimus) DNA in fecal extracts. We test the assay on pure polar bear DNA extracted from muscle tissue and find a high correlation between fluorometric and qPCR quantifications. The qPCR assay was also successfully used to quantify the amount of DNA derived from polar bears in fecal extractions. Orthologs of the F2 gene have been identified across vertebrates; thus, similar qPCR assays could be developed for other species to enable noninvasive studies. © 2020 Hayward et al.Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 is an emerging gene-editing technology that is widely used in prokaryotes and eukaryotes. It can realize the specific manipulation of the genome efficiently and accurately. CRISPR/Cas9 coupled λ-Red recombination technology was used to perform genome editing in different genes. For finding an efficient method to edit the virulence genes of enterotoxigenic E. coli (ETEC), the two-plasmid system was used. Selleck Navitoclax The coding sequence (CDS) region of the estA, eltI, estB, eltIIc1, and faeG locus were deleted. The coding region of estB was substituted with estA. Selleck Navitoclax Gene recombination efficiency ranged from 0 to 77.78% when the length of the homology arm was from 50 to 300 bp. Within this range, the longer the homology arm, the higher the efficiency of genetic recombination. The results showed that this system can target virulence genes located in plasmids and on chromosomes of ETEC strains. A single base mutation was performed by two-step gene fragment replacement. This study lays the foundation for research on virulence factors and genetic engineering of vaccines for ETEC. ©2020 Hou et al.Seagrass beds provide a variety of ecosystem services, both within and outside the bounds of the habitat itself. Here we use environmental DNA (eDNA) amplicons to analyze a broad cross-section of taxa from ecological communities in and immediately surrounding eelgrass (Zostera marina). Sampling seawater along transects extending alongshore outward from eelgrass beds, we demonstrate that eDNA provides meter-scale resolution of communities in the field. We evaluate eDNA abundance indices for 13 major phylogenetic groups of marine and estuarine taxa along these transects, finding highly local changes linked with proximity to Z. marina for a diverse group of dinoflagellates, and for no other group of taxa. Eelgrass habitat is consistently associated with dramatic reductions in dinoflagellate abundance both within the contiguous beds and for at least 15 m outside, relative to nearby sites without eelgrass. These results are consistent with the hypothesis that eelgrass-associated communities have allelopathic effects on dinoflagellates, and that these effects can extend in a halo beyond the bounds of the contiguous beds. Because many dinoflagellates are capable of forming harmful algal blooms (HABs) toxic to humans and other animal species, the apparent salutary effect of eelgrass habitat on neighboring waters has important implications for public health as well as shellfish aquaculture and harvesting. © 2020 Jacobs-Palmer et al.Allium tenuissimum L. is a widely distributed perennial herbaceous species in temperate and desert steppes. Relative to other wild Allium species, it produces unique sweet flavors, more biomass in arid and cold environments, and has generated greater interest for crop production. Successful crop establishment, however, will depend on rapid and uniform seed germination. Our study aimed to characterize seed germination of A. tenuissimum under various temperature regimes (11, 15, 20, 24 and 28 °C) and water potential levels (0, -0.2, -0.4 and -0.6 MPa), and model germination by hydrotime (HT) and hydrothermal time (HTT) analysis. Final germination percentage (FGP) increased within the range of 11 to 20 °C, yet it declined within the range of 24 to 28 °C and generally decreased as water potential became more negative within each temperature setting. Maximum FGP was observed at 20 °C at all water potential settings and ranged from 55.0 ± 5.3 to 94.8 ± 1.4%. According to HT and HTT models, the base (T b) and optimum temperatures (T o) for seed germination were 7.0 and 20.5 °C, respectively. In addition, base water potential for the fraction of germination within the seed lot (Ψb(g)) shifted to 0 MPa as temperature increased from T b to ceiling temperature (T c). For obtaining 50 % seed germination, Ψb(50) and T c(50) were estimated to be -0.67 MPa and 27.2 °C, respectively. These values for T b and Ψb(50) suggest seed germination of A. tenuissimum is both cold and drought tolerant and suitable for production in semi-arid regions. Our characterization of the ideal sowing conditions for A. tenuissimum, i.e., 20.5 °C and soil water potential less negative than -0.67 MPa offers information to forecast suitable settings to enhance crop production. ©2020 Xiao et al.Accurate identification of ligand-binding pockets in a protein is important for structure-based drug design. In recent years, several deep learning models were developed to learn important physical-chemical and spatial information to predict ligand-binding pockets in a protein. However, ranking the native ligand binding pockets from a pool of predicted pockets is still a hard task for computational molecular biologists using a single web-based tool. Hence, we believe, by using closer to real application data set as training and by providing ligand information, an enhanced model to identify accurate pockets can be obtained. In this article, we propose a new deep learning method called DeepBindPoc for identifying and ranking ligand-binding pockets in proteins. The model is built by using information about the binding pocket and associated ligand. We take advantage of the mol2vec tool to represent both the given ligand and pocket as vectors to construct a densely fully connected layer model. During the training, important features for pocket-ligand binding are automatically extracted and high-level information is preserved appropriately.
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