133 research outputs found

    Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions

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    BACKGROUND: Shape complementarity and non-covalent interactions are believed to drive protein-ligand interaction. To date protein-protein, protein-DNA, and protein-RNA interactions were systematically investigated, which is in contrast to interactions with small ligands. We investigate the role of covalent and non-covalent bonds in protein-small ligand interactions using a comprehensive dataset of 2,320 complexes. METHODOLOGY AND PRINCIPAL FINDINGS: We show that protein-ligand interactions are governed by different forces for different ligand types, i.e., protein-organic compound interactions are governed by hydrogen bonds, van der Waals contacts, and covalent bonds; protein-metal ion interactions are dominated by electrostatic force and coordination bonds; protein-anion interactions are established with electrostatic force, hydrogen bonds, and van der Waals contacts; and protein-inorganic cluster interactions are driven by coordination bonds. We extracted several frequently occurring atomic-level patterns concerning these interactions. For instance, 73% of investigated covalent bonds were summarized with just three patterns in which bonds are formed between thiol of Cys and carbon or sulfur atoms of ligands, and nitrogen of Lys and carbon of ligands. Similar patterns were found for the coordination bonds. Hydrogen bonds occur in 67% of protein-organic compound complexes and 66% of them are formed between NH- group of protein residues and oxygen atom of ligands. We quantify relative abundance of specific interaction types and discuss their characteristic features. The extracted protein-organic compound patterns are shown to complement and improve a geometric approach for prediction of binding sites. CONCLUSIONS AND SIGNIFICANCE: We show that for a given type (group) of ligands and type of the interaction force, majority of protein-ligand interactions are repetitive and could be summarized with several simple atomic-level patterns. We summarize and analyze 10 frequently occurring interaction patterns that cover 56% of all considered complexes and we show a practical application for the patterns that concerns interactions with organic compounds

    Assessing an organizational culture instrument based on the Competing Values Framework: Exploratory and confirmatory factor analyses

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    BACKGROUND: The Competing Values Framework (CVF) has been widely used in health services research to assess organizational culture as a predictor of quality improvement implementation, employee and patient satisfaction, and team functioning, among other outcomes. CVF instruments generally are presented as well-validated with reliable aggregated subscales. However, only one study in the health sector has been conducted for the express purpose of validation, and that study population was limited to hospital managers from a single geographic locale. METHODS: We used exploratory and confirmatory factor analyses to examine the underlying structure of data from a CVF instrument. We analyzed cross-sectional data from a work environment survey conducted in the Veterans Health Administration (VHA). The study population comprised all staff in non-supervisory positions. The survey included 14 items adapted from a popular CVF instrument, which measures organizational culture according to four subscales: hierarchical, entrepreneurial, team, and rational. RESULTS: Data from 71,776 non-supervisory employees (approximate response rate 51%) from 168 VHA facilities were used in this analysis. Internal consistency of the subscales was moderate to strong (α = 0.68 to 0.85). However, the entrepreneurial, team, and rational subscales had higher correlations across subscales than within, indicating poor divergent properties. Exploratory factor analysis revealed two factors, comprising the ten items from the entrepreneurial, team, and rational subscales loading on the first factor, and two items from the hierarchical subscale loading on the second factor, along with one item from the rational subscale that cross-loaded on both factors. Results from confirmatory factor analysis suggested that the two-subscale solution provides a more parsimonious fit to the data as compared to the original four-subscale model. CONCLUSION: This study suggests that there may be problems applying conventional CVF subscales to non-supervisors, and underscores the importance of assessing psychometric properties of instruments in each new context and population to which they are applied. It also further highlights the challenges management scholars face in assessing organizational culture in a reliable and comparable way. More research is needed to determine if the emergent two-subscale solution is a valid or meaningful alternative and whether these findings generalize beyond VHA

    The Influence of Recent Climate Change on Tree Height Growth Differs with Species and Spatial Environment

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    Tree growth has been reported to increase in response to recent global climate change in controlled and semi-controlled experiments, but few studies have reported response of tree growth to increased temperature and atmospheric carbon dioxide (CO2) concentration in natural environments. This study addresses how recent global climate change has affected height growth of trembling aspen (Populus tremuloides Michx) and black spruce (Picea mariana Mill B.S.) in their natural environments. We sampled 145 stands dominated by aspen and 82 dominated by spruce over the entire range of their distributions in British Columbia, Canada. These stands were established naturally after fire between the 19th and 20th centuries. Height growth was quantified as total heights of sampled dominant and co-dominant trees at breast-height age of 50 years. We assessed the relationships between 50-year height growth and environmental factors at both spatial and temporal scales. We also tested whether the tree growth associated with global climate change differed with spatial environment (latitude, longitude and elevation). As expected, height growth of both species was positively related to temperature variables at the regional scale and with soil moisture and nutrient availability at the local scale. While height growth of trembling aspen was not significantly related to any of the temporal variables we examined, that of black spruce increased significantly with stand establishment date, the anomaly of the average maximum summer temperature between May-August, and atmospheric CO2 concentration, but not with the Palmer Drought Severity Index. Furthermore, the increase of spruce height growth associated with recent climate change was higher in the western than in eastern part of British Columbia. This study demonstrates that the response of height growth to recent climate change, i.e., increasing temperature and atmospheric CO2 concentration, did not only differ with tree species, but also their growing spatial environment

    Cloning and Characterization of Maize miRNAs Involved in Responses to Nitrogen Deficiency

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    Although recent studies indicated that miRNAs regulate plant adaptive responses to nutrient deprivation, the functional significance of miRNAs in adaptive responses to nitrogen (N) limitation remains to be explored. To elucidate the molecular biology underlying N sensing/signaling in maize, we constructed four small RNA libraries and one degradome from maize seedlings exposed to N deficiency. We discovered a total of 99 absolutely new loci belonging to 47 miRNA families by small RNA deep sequencing and degradome sequencing, as well as 9 new loci were the paralogs of previously reported miR169, miR171, and miR398, significantly expanding the reported 150 high confidence genes within 26 miRNA families in maize. Bioinformatic and subsequent small RNA northern blot analysis identified eight miRNA families (five conserved and three newly identified) differentially expressed under the N-deficient condition. Predicted and degradome-validated targets of the newly identified miRNAs suggest their involvement in a broad range of cellular responses and metabolic processes. Because maize is not only an important crop but is also a genetic model for basic biological research, our research contributes to the understanding of the regulatory roles of miRNAs in plant adaption to N-deficiency stress

    Genome-Wide Identification of MicroRNAs in Response to Low Nitrate Availability in Maize Leaves and Roots

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    BACKGROUND: Nitrate is the major source of nitrogen available for many crop plants and is often the limiting factor for plant growth and agricultural productivity especially for maize. Many studies have been done identifying the transcriptome changes under low nitrate conditions. However, the microRNAs (miRNAs) varied under nitrate limiting conditions in maize has not been reported. MiRNAs play important roles in abiotic stress responses and nutrient deprivation. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we used the SmartArray™ and GeneChip® microarray systems to perform a genome-wide search to detect miRNAs responding to the chronic and transient nitrate limiting conditions in maize. Nine miRNA families (miR164, miR169, miR172, miR397, miR398, miR399, miR408, miR528, and miR827) were identified in leaves, and nine miRNA families (miR160, miR167, miR168, miR169, miR319, miR395, miR399, miR408, and miR528) identified in roots. They were verified by real time stem loop RT-PCR, and some with additional time points of nitrate limitation. The miRNAs identified showed overlapping or unique responses to chronic and transient nitrate limitation, as well as tissue specificity. The potential target genes of these miRNAs in maize were identified. The expression of some of these was examined by qRT-PCR. The potential function of these miRNAs in responding to nitrate limitation is described. CONCLUSIONS/SIGNIFICANCE: Genome-wide miRNAs responding to nitrate limiting conditions in maize leaves and roots were identified. This provides an insight into the timing and tissue specificity of the transcriptional regulation to low nitrate availability in maize. The knowledge gained will help understand the important roles miRNAs play in maize responding to a nitrogen limiting environment and eventually develop strategies for the improvement of maize genetics

    Satellite-based terrestrial production efficiency modeling

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    Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research

    Substrate Specifity Profiling of the Aspergillus fumigatus Proteolytic Secretome Reveals Consensus Motifs with Predominance of Ile/Leu and Phe/Tyr

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    The filamentous fungus Aspergillus fumigatus (AF) can cause devastating infections in immunocompromised individuals. Early diagnosis improves patient outcomes but remains challenging because of the limitations of current methods. To augment the clinician's toolkit for rapid diagnosis of AF infections, we are investigating AF secreted proteases as novel diagnostic targets. The AF genome encodes up to 100 secreted proteases, but fewer than 15 of these enzymes have been characterized thus far. Given the large number of proteases in the genome, studies focused on individual enzymes may overlook potential diagnostic biomarkers.As an alternative, we employed a combinatorial library of internally quenched fluorogenic probes (IQFPs) to profile the global proteolytic secretome of an AF clinical isolate in vitro. Comparative protease activity profiling revealed 212 substrate sequences that were cleaved by AF secreted proteases but not by normal human serum. A central finding was that isoleucine, leucine, phenylalanine, and tyrosine predominated at each of the three variable positions of the library (44.1%, 59.1%, and 57.0%, respectively) among substrate sequences cleaved by AF secreted proteases. In contrast, fewer than 10% of the residues at each position of cleaved sequences were cationic or anionic. Consensus substrate motifs were cleaved by thermostable serine proteases that retained activity up to 50°C. Precise proteolytic cleavage sites were reliably determined by a simple, rapid mass spectrometry-based method, revealing predominantly non-prime side specificity. A comparison of the secreted protease activities of three AF clinical isolates revealed consistent protease substrate specificity fingerprints. However, secreted proteases of A. flavus, A. nidulans, and A. terreus strains exhibited striking differences in their proteolytic signatures.This report provides proof-of-principle for the use of protease substrate specificity profiling to define the proteolytic secretome of Aspergillus fumigatus. Expansion of this technique to protease secretion during infection could lead to development of novel approaches to fungal diagnosis
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