The cytidylyltransferase superfamily: Identification of the nucleotide-binding site and fold prediction

The crystal structure of glycerol-3-phosphate cytidylyltransferase from B. subtilis (TagD) is about to be solved. Here, we report a testable structure prediction based on the identification by sequence analysis of a superfamily of functionally diverse but structurally similar nucleotide-binding enzymes. We predict that TagD is a member of this family. The most conserved region in this superfamily resembles the ATP-binding HiGH motif of class I aminoacyI-tRNA synthetases. The predicted secondary structure of cytidylyltransferase and its homologues is compatible with the α/β topography of the class I aminoacyl-tRNA synthetases. The hypothesis of similarity of fold is strengthened by sequence-structure alignment and 3D model building using the known structure of tyrosyl tRNA synthetase as template. The proposed 3D model of TagD is plausible both structurally, with a well packed hydrophobic core, and functionally, as the most conserved residues cluster around the putative nucleotide binding site. If correct, the model would imply a very ancient evolutionary link between class I tRNA synthetases and the novel cytidylyltransferase superfamily. © 1995 Wiley-Liss, Inc.     

Modeling WEPP erodibility parameters in calcareous soils in northwest Iran

Modeling soil detachment rates at the regional scale is important for better understanding of the processes of erosion and the development of erosion models. Soil erodibility is an important factor for predicting soil loss, but its direct measurement at the watershed scale is difficult, time-consuming and costly. This study used stepwise multiple-linear regression (MLR) and artificial neural networks (ANNs) to model Water Erosion Prediction Project (WEPP) soil erodibility parameters, including the baseline inter-rill erodibility (K_ib), baseline rill erodibility (K_rb) and critical shear stress (τ_cb) of cropland conditions in calcareous soils of northwest Iran. Simulated inter-rill and rill erosion experiments were conducted at 100 locations with three replications. K_ib, K_rb and τ_cb and basic soil properties were measured at each location. Auxiliary variables related to soil erodibility were derived from a Landsat 7 satellite image and a 30 m × 30 m digital elevation model (DEM). MLR and ANN models were employed to predict K_ib, K_rb and τ_cb using two groups of input variables: i) more easily measurable basic soil properties (pedo-transfer functions (PTFs)) and ii) more easily measurable basic soil properties and auxiliary data (soil spatial prediction functions (SSPFs)). The results indicated that the WEPP models performed poorly in comparison to the derived models. PTFs and SSPFs generated from ANN models provided more reliable predictions than the MLR models. ANN-based SSPF models yielded the best results (with the highest R² and lowest RMSE values) for predicting Kib and Krb. ANN-based PTF model performed reasonably well for predicting τ_cb. These results show that information from terrain attributes and remote sensing data are potential auxiliary variables for improving prediction of soil erodibility parameters.     

细菌sRNA数据库

细菌sRNA是一类长度在50～500 nt的调控小RNA（small regulatory RNA）,主要通过与靶标mRNA或靶标蛋白质结合发挥多种生物学功能。目前,随着生物信息学与高通量测序的应用,发现了越来越多的细菌sRNA,开发了多个相关数据库。为了sRNA工作者系统了解与应用这些数据,本文拟对包含细菌sRNA的综合数据库和细菌sRNA专业数据库作一概述,并对sRNA数据库的未来发展进行展望。     

Chromatographic retention time prediction for posttranslationally modified peptides

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for mass spectrometry-based proteomics, especially in designing more efficient procedures for state-of-the-art targeted workflows. Additionally, accurate retention time predictions can also be used to increase confidence in identifications in shotgun experiments. Despite these obvious benefits, the use of such methods has so far not been extended to (posttranslationally) modified peptides due to the absence of efficient predictors for such peptides. We here therefore describe a new retention time predictor for modified peptides, built on the foundations of our existing Elude algorithm. We evaluated our software by applying it on five types of commonly encountered modifications. Our results show that Elude now yields equally good prediction performances for modified and unmodified peptides, with correlation coefficients between predicted and observed retention times ranging from 0.93 to 0.98 for all the investigated datasets. Furthermore, we show that our predictor handles peptides carrying multiple modifications as well. This latest version of Elude is fully portable to new chromatographic conditions and can readily be applied to other types of posttranslational modifications. Elude is available under the permissive Apache2 open source License at http://per-colator.com or can be run via a web-interface at http://elude.sbc.su.se.     

The AutoDock suite at 30

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third‐party developers.     

Validation of discrete time-to-event prediction models in the presence of competing risks

Clinical prediction models play a key role in risk stratification, therapy assignment and many other fields of medical decision making. Before they can enter clinical practice, their usefulness has to be demonstrated using systematic validation. Methods to assess their predictive performance have been proposed for continuous, binary, and time-to-event outcomes, but the literature on validation methods for discrete time-to-event models with competing risks is sparse. The present paper tries to fill this gap and proposes new methodology to quantify discrimination, calibration, and prediction error (PE) for discrete time-to-event outcomes in the presence of competing risks. In our case study, the goal was to predict the risk of ventilator-associated pneumonia (VAP) attributed to Pseudomonas aeruginosa in intensive care units (ICUs). Competing events are extubation, death, and VAP due to other bacteria. The aim of this application is to validate complex prediction models developed in previous work on more recently available validation data.     

In vitro organogenesis of Citrus volkameriana and Citrus aurantium

In vitro organogenesis of Citrus volkameriana and C. aurantium was studied considering three explant types: epicotyl segment, internodal segment, and hypocotyl segment with attached cotyledon fragment. The explants were cultured in medium according to Grosser and Gmitter (EME) supplemented with 0, 0.5, 1.0, 1.5, and 2.0 mg dm^{− 3} 6-benzyl-aminopurine (BAP), incubated firstly in darkness for 4 weeks, and then transferred to 16-h photoperiod for 2 weeks. Comparing epicotyl and internodal segments, a higher percentage of responsive explants and a higher number of shoots per explant were obtained with epicotyl segments, regardless of the BAP concentration. For C. volkameriana the highest percentage of responsive epicotyl segments (42 %) was obtained in EME with 1.0 mg dm⁻³ BAP, while for C. aurantium (59 %) in EME with 0.5 mg dm⁻³ BAP. The organogenesis efficiency was the best with the use of the hypocotyl segment with attached cotyledon fragment (77 % for C. volkameriana and to 75 % for C. aurantium). With this explant the morphogenesis occurred only in the hypocotyl region. The in vitro organogenesis was characterized by histological analyses showing that the morphogenic process started in the cambium region near the explant cut end.     

南亚热带常绿阔叶林林下层植物的生物量及其测定方法的探讨

应用全收割法测定广东省鼎湖山南亚热带常绿阔叶林林下层植物生物量 ,林下植物总生物量为 12 9 58g/m2 ,其中茎、枝、叶、根的生物量占总生物量的比例约为 4 0 % ,9 0 % ,2 2 % ,2 9% .由部分实测数据建立林下植物个体生物量估算模型为W =0 0 0 4 2 ·H1 932 3.应用该模型得到的估算值 ,与收获实测值的相对误差仅为 1 8% ,具有良好的精度 .此外 ,还通过改变取样面积对该模型的适用性进行了探讨 .     

中国人均生态足迹与生物承载力变化的EMD分析及情景预测

利用经验模态分解(EMD)方法分解并提取1961～2001年中国人均生态足迹与生物承载力变化的波动周期,建立具有周期性波动的非线性动力学预测模型,提出未来50a中国人均生态足迹和生物承载力变化的3种预测情景。结果表明:(1)40a来,中国人均生态足迹在波动中不断增加,具有明显的3.5a和8a两个波动周期;中国人均生物承载力在波动中不断减少,具有明显的2.7a和28a两个周期。(2)若一切照旧,即未来50a中国人均生态足迹与生物承载力保持过去40a的年均变化率不变,则人均生态足迹会持续上升,2050年达到3.391g.hm2;人均生物承载力持续下降,2050年降为0.490g.hm2;而人均生态赤字急剧拉大,2050年为3.024g.hm2,可持续发展形势非常严峻。(3)若缓慢变化,即未来20a中国人均生态足迹保持年均增长率1.195%、人均生物承载力年均减少率0.614%不变,则2025年人均生态足迹为1.849g.hm2、人均生物承载力为0.860g.hm2、人均赤字0.989g.hm2。(4)若人均生态足迹快速减少,即2025～2050年中国人均生态足迹年均减少率为0.996%、人均生物承载力年均减少率为0.614%不变,则2050年人均生态足迹为1.381g.hm2、人均生物承载力0.739g.hm2、人均生态赤字0.641g.hm2,但这需要中国经济发展和技术水平的极大提高、能源消费结构的多元化、居民消费意识和消费模式的快速转变、人民生活质量的极大改善。这样,中国的生态发展才有助于实现全球水平的生态可持续发展,在促进世界可持续发展的道路上起到积极的推动作用。