Molecules, development and fossils in the study of metazoan evolution; Articulata versus Ecdysozoa revisited

Two conflicting hypotheses of protostome relationships, Articulata and Ecdysozoa, are reviewed by evaluating the evidence in favor and against each one of them. Understanding early embryonic development and segmentation in non-arthropod non-annelid protostomes seems crucial to the debate. New ways of coding metazoan matrices, avoiding ground-patterns and higher taxa, and incorporating fossil evidence seems the best way to avoid circular debates. Molecular data served as the catalyzer for the Ecdysozoa hypothesis, although morphological support had been implicitly suggested. Most molecular analyses published so far have shown some support for Ecdysozoa, whereas none has ever supported Articulata. Here, new analyses of up to four nuclear loci, including 18S rRNA, myosin heavy chain II, histone H3 and elongation factor 1- are conducted to test the molecular support for Ecdysozoa, and, at least under some parameter sets, most data sets show a clade formed by the molting animals. In contrast, support for Articulata is not found under any analytical conditions.     

PRIMSIPLR: Prediction of inner‐membrane situated pore‐lining residues for alpha‐helical transmembrane proteins

Transmembrane proteins such as transporters and channels mediate the passage of inorganic and organic substances across biological membranes through their central pore. Pore‐lining residues (PLRs) that make direct contacts to the substrates have a crucial impact on the function of the protein and, hence, their identification is a key step in mechanistic studies. Here, we established a nonredundant data set containing the three‐dimensional (3D) structures of 90 α‐helical transmembrane proteins and annotated the PLRs of these proteins by a pore identification software. A support vector machine was then trained to distinguish PLRs from other residues based on the protein sequence alone. Using sixfold cross‐validation, our best performing predictor gave a Matthews's correlation coefficient of 0.41 with an accuracy of 0.86, sensitivity of 0.61, and specificity of 0.89, respectively. We provide a novel software tool that will aid biomedical scientists working on transmembrane proteins with unknown 3D structures. Both standalone version and web service are freely available from the URL http://service.bioinformatik.uni-saarland.de/PRIMSIPLR/ . Proteins 2014; 82:1503–1511. © 2014 Wiley Periodicals, Inc.     

BCL::Fold—Protein topology determination from limited NMR restraints

When experimental protein NMR data are too sparse to apply traditional structure determination techniques, de novo protein structure prediction methods can be leveraged. Here, we describe the incorporation of NMR restraints into the protein structure prediction algorithm BCL::Fold. The method assembles discreet secondary structure elements using a Monte Carlo sampling algorithm with a consensus knowledge‐based energy function. New components were introduced into the energy function to accommodate chemical shift, nuclear Overhauser effect, and residual dipolar coupling data. In particular, since side chains are not explicitly modeled during the minimization process, a knowledge based potential was created to relate experimental side chain proton–proton distances to C_β–C_β distances. In a benchmark test of 67 proteins of known structure with the incorporation of sparse NMR restraints, the correct topology was sampled in 65 cases, with an average best model RMSD100 of 3.4 ± 1.3 Å versus 6.0 ± 2.0 Å produced with the de novo method. Additionally, the correct topology is present in the best scoring 1% of models in 61 cases. The benchmark set includes both soluble and membrane proteins with up to 565 residues, indicating the method is robust and applicable to large and membrane proteins that are less likely to produce rich NMR datasets. Proteins 2014; 82:587–595. © 2013 Wiley Periodicals, Inc.     

Molecular simulation of drug-binding kinetics

Early drug discovery often focuses on improving drug–receptor binding thermodynamics without considering drug-binding kinetics. This article first reviews some experiments and pathway simulations that point to the significance of considering drug-binding kinetics in drug discovery. It then describes our development and application of a molecular dynamics-based mining-minima approach to studying drug-binding kinetics, with the goal of aiding the design of drug candidates with certain desired binding kinetics. Discussions on further refinement of this approach with the Feynman path integral formalism then follow.     

Satellite remote sensing,biodiversity research and conservation of the future

Assessing and predicting ecosystem responses to global environmental change and its impacts on human well-being are high priority targets for the scientific community. The potential for synergies between remote sensing science and ecology, especially satellite remote sensing and conservation biology, has been highlighted by many in the past. Yet, the two research communities have only recently begun to coordinate their agendas. Such synchronization is the key to improving the potential for satellite data effectively to support future environmental management decision-making processes. With this themed issue, we aim to illustrate how integrating remote sensing into ecological research promotes a better understanding of the mechanisms shaping current changes in biodiversity patterns and improves conservation efforts. Added benefits include fostering innovation, generating new research directions in both disciplines and the development of new satellite remote sensing products.     

The complete chloroplast genome sequence of Taxus chinensis var. mairei (Taxaceae): loss of an inverted repeat region and comparative analysis with related species

Taxus chinensis var. mairei (Taxaceae) is a domestic variety of yew species in local China. This plant is one of the sources for paclitaxel, which is a promising antineoplastic chemotherapy drugs during the last decade. We have sequenced the complete nucleotide sequence of the chloroplast (cp) genome of T. chinensis var. mairei. The T. chinensis var. mairei cp genome is 129,513 bp in length, with 113 single copy genes and two duplicated genes (trnI-CAU, trnQ-UUG). Among the 113 single copy genes, 9 are intron-containing. Compared to other land plant cp genomes, the T. chinensis var. mairei cp genome has lost one of the large inverted repeats (IRs) found in angiosperms, fern, liverwort, and gymnosperm such as Cycas revoluta and Ginkgo biloba L. Compared to related species, the gene order of T. chinensis var. mairei has a large inversion of ~ 110 kb including 91 genes (from rps18 to accD) with gene contents unarranged. Repeat analysis identified 48 direct and 2 inverted repeats 30 bp long or longer with a sequence identity greater than 90%. Repeated short segments were found in genes rps18, rps19 and clpP. Analysis also revealed 22 simple sequence repeat (SSR) loci and almost all are composed of A or T.     

湘南某矿区蔬菜中Pb、Cd污染状况及健康风险评估

通过采集湘南某矿区周边农田中种植的蔬菜和对应耕作层土壤样品,探究了农田蔬菜Pb、Cd的污染状况,蔬菜和土壤重金属含量之间的相关性,蔬菜中重金属对人体的健康风险。结果表明:(1)污染区土壤重金属污染非常严重,叶菜类蔬菜重金属超出了食品卫生标准限值,但是果菜类蔬菜中重金属没有超出食品卫生标准限值。(2)不同蔬菜不同器官所含Pb、Cd有明显差异;不同种类蔬菜Pb、Cd含量不同,一般是叶菜类果菜类;同种蔬菜不同部位重金属含量的顺序也不同,一般为根茎叶果,或根叶茎果。(3)二类蔬菜中重金属Pb、Cd的富集系数顺序为叶菜类果菜类。(4)蔬菜中Pb、Cd含量与土壤中相对应元素含量均无显著相关性。(5)就农产品安全性而言,果菜类蔬菜比叶菜类蔬菜更适合在此矿区栽培。     

采煤塌陷区不同地貌类型植物群落多样性变化及其与土壤理化性质的关系

通过对神府-东胜矿区2种不同地貌类型下沉陷样地及对照样地地表植被进行调查,研究不同地貌类型、不同沉陷位置的群落多样性变化及其与土壤理化性质的关系。研究结果表明:(1)哈拉沟矿区(黄土丘陵地貌)植物种类较丰富,大柳塔矿区(风沙地貌)植被种类较单一;达乌里胡枝子作为风沙地貌沉陷区指示物种,其演替机制符合忍耐作用理论,紫翅猪毛菜作为黄土丘陵沟壑地貌沉陷区指示物种,其演替机制是促进理论和竞争共同作用的结果。(2)沉陷干扰12a后,2个研究区Shannon-Wiener指数分别增加了54.60%,73.85%,风沙地貌研究区土壤含水量和脲酶活性分别增加了8.64%和57.14%,黄土丘陵沟壑地貌研究区土壤有机质增加了47.73%。(3)采煤塌陷后,风沙地貌矿区坡中位置过氧化氢酶活性下降63.50%,土壤体积含水量降低58.70%,植物群落多样性显著降低;坡底位置土壤含水量、土壤养分、植物群落多样性均显著提高,土壤理化性质和植物群落多样性变化协同一致。(4)风沙地貌区植物群落多样性与土壤含水量存在显著正相关关系,黄土丘陵沟壑地貌区植物群落多样性与土壤有机质含量存在显著负相关关系。     

Recent advances in biocatalyst discovery,development and applications

Enzymes catalyze a wide range of biotransformations and have a great potential as environmentally friendly alternatives to classical chemical catalysts in various industrial applications. Recently, advanced techniques and strategies in enzyme discovery and engineering have led to the significant expansion of the quantity and functional diversity of biocatalysts, which has further allowed broader uses of biocatalysts in new processes, especially those traditionally enabled only by chemical catalysts. Here we highlight some of these recent advances with the focus on new approaches in biocatalyst discovery and development, and discuss new applications of selected biocatalysts including transaminases, cytochrome P450s, and Baeyer–Villiger monooxygenases.