Discrimination between distant homologs and structural analogs: lessons from manually constructed, reliable data sets

A natural way to study protein sequence, structure, and function is to put them in the context of evolution. Homologs inherit similarities from their common ancestor, while analogs converge to similar structures due to a limited number of energetically favorable ways to pack secondary structural elements. Using novel strategies, we previously assembled two reliable databases of homologs and analogs. In this study, we compare these two data sets and develop a support vector machine (SVM)-based classifier to discriminate between homologs and analogs. The classifier uses a number of well-known similarity scores. We observe that although both structure scores and sequence scores contribute to SVM performance, profile sequence scores computed based on structural alignments are the best discriminators between remote homologs and structural analogs. We apply our classifier to a representative set from the expert-constructed database, Structural Classification of Proteins (SCOP). The SVM classifier recovers 76% of the remote homologs defined as domains in the same SCOP superfamily but from different families. More importantly, we also detect and discuss interesting homologous relationships between SCOP domains from different superfamilies, folds, and even classes.     

Structural robustness of metabolic networks with respect to multiple knockouts

We present a generalised framework for analysing structural robustness of metabolic networks, based on the concept of elementary flux modes (EFMs). Extending our earlier study on single knockouts [Wilhelm, T., Behre, J., Schuster, S., 2004. Analysis of structural robustness of metabolic networks. IEE Proc. Syst. Biol. 1(1), 114-120], we are now considering the general case of double and multiple knockouts. The robustness measures are based on the ratio of the number of remaining EFMs after knockout vs. the number of EFMs in the unperturbed situation, averaged over all combinations of knockouts. With the help of simple examples we demonstrate that consideration of multiple knockouts yields additional information going beyond single-knockout results. It is proven that the robustness score decreases as the knockout depth increases.We apply our extended framework to metabolic networks representing amino acid anabolism in Escherichia coli and human hepatocytes, and the central metabolism in human erythrocytes. Moreover, in the E. coli model the two subnetworks synthesising amino acids that are essential and those that are non-essential for humans are studied separately. The results are discussed from an evolutionary viewpoint. We find that E. coli has the most robust metabolism of all the cell types studied here. Considering only the subnetwork of the synthesis of non-essential amino acids, E. coli and the human hepatocyte show about the same robustness.     

不同耕作措施对黄土高原旱地土壤呼吸的影响

在甘肃省定西市李家堡镇设置不同耕作措施试验,对春小麦、豌豆双序列轮作下的土壤呼吸及其对应时间的冠层温度、土壤水分进行了测定.结果表明：春小麦和豌豆在整个生育期内的土壤呼吸都表现出不同的变化趋势,春小麦地土壤呼吸在拔节前期、灌浆期和收后分别达到高峰期;豌豆地土壤呼吸在五叶期、吐丝期、开花结荚期和收后分别达到高峰期.免耕秸秆覆盖处理和传统耕作处理下春小麦地土壤呼吸日变化明显,免耕秸秆覆盖处理明显低于传统耕作处理;而豌豆地土壤呼吸日变化不明显.春小麦和豌豆冠层温度均与土壤呼吸呈显著线性相关,春小麦孕穗期相关性最高,灌浆期次之;豌豆开花结荚期相关性最高,分枝期次之.土壤含水量与土壤呼吸间存在极显著的凸型抛物线型相关,保护性耕作下的相关性都高于传统耕作,其中免耕秸秆覆盖处理的春小麦地和豌豆地土壤含水量与土壤呼吸的相关性在各层次土壤中均为最高,10～30 cm土壤含水量对春小麦地土壤呼吸的影响最大,5～10 cm土壤含水量对豌豆地土壤呼吸的影响最大.与传统耕作相比,免耕秸秆覆盖、免耕、传统耕作秸秆还田、传统耕作结合地膜覆盖、免耕结合地膜覆盖5种保护性耕作措施都能不同程度地降低土壤呼吸,其中免耕秸秆覆盖优势最明显.     

生物多样性评价软件BiodiversityMapping的设计与实现

针对目前国内生物多样性相关软件缺乏的情况,利用可视化开发方法和地理信息系统组件包shape Viewer Objects开发了一个综合性的生物多样性评价软件BiodiversityMapping。该软件运行于Windows98／NT操作系统下,是一个32位Windows应用软件;可以计算8类37种d、D生物多样性测度并能利用地理信息系统技术将结果空间化表达。利用该软件计算了北京东灵山地区3个研究区域(小龙门、梨园岭和东灵山主峰)内11个生境中大步甲属(Carabus)昆虫的Shannon-Wiener多样性指数并制图,然后对这3个地区进行了右尾和排序。结果表明,BiodjversityMapping软件能够准确方便地计算多种生物多样性测度,是生物多样性评价的一个有力工具。     

A simulation framework for modeling anthropogenic disturbances in habitat networks

Anthropogenic disturbances, like roads, increase the landscape fragmentation and affect wildlife migration and biodiversity. Such disturbances often prevent migration of wildlife due to increased barriers and mortality effects.

The aim of our simulation based approach is to assess the landscape permeability considering anthropogenic disturbances. The developed framework SimapD imposes an abstract view of a habitat network, based on an undirected graph. The simulation is done by an individual-oriented approach, where individuals explore the idealized network. Based on the information gained during the simulation, an overall network permeability index is calculated, which can be used to compare different scenarios of landscape development. Disturbances are represented by sub-models, from which appropriate resistance and mortality rates can be deduced. In this paper this is demonstrated by the construction of a fuzzy road kill model for the federal state of Baden-Wuerttemberg, Germany. The utilization of the network permeability index and a comparison to other fragmentation measures is shown by an exemplary application.     

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment

Profile hidden Markov models （HMMs） based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.     

Quantifying successional changes in response to forest disturbances

Question: Can dissimilarity measures of individual plots be used to forecast the driving factors among various anthropogenic disturbances influencing understorey successional changes? Location: Yambulla State Forest, south‐eastern Australia (37°14'S, 149°38'E). Methods: Assessments of understorey vegetation communities were taken prior to anthropogenic disturbances and at three subsequent time periods representing a period of 15 years post‐disturbance. Dissimilarities were calculated from the original assessment and modelled in a Bayesian framework to examine the influence of logging, number of prescribed burns and time. Results: All sites underwent significant changes over time independently of the imposed management regimes. Logging resulted in an immediate change in vegetation assemblage which decreased in the subsequent assessments. The number of prescribed fires brought greater change in the shrub vegetation assemblages, but less change in the ground species vegetation assemblages. Conclusions: The anthropogenic disturbances did have some role in the changes of vegetation assemblages but these were minimal. The ongoing changes appear to be a natural response to the last wildfire, which passed through the study area in 1973 (13 years prior to the study). Forest management practices should consider the influence of wildfire succession when planning for the conservation of biodiversity.     

A systematic analysis of scoring functions in rigid‐body protein docking: The delicate balance between the predictive rate improvement and the risk of overtraining

Protein‐protein interactions play fundamental roles in biological processes including signaling, metabolism, and trafficking. While the structure of a protein complex reveals crucial details about the interaction, it is often difficult to acquire this information experimentally. As the number of interactions discovered increases faster than they can be characterized, protein‐protein docking calculations may be able to reduce this disparity by providing models of the interacting proteins. Rigid‐body docking is a widely used docking approach, and is often capable of generating a pool of models within which a near‐native structure can be found. These models need to be scored in order to select the acceptable ones from the set of poses. Recently, more than 100 scoring functions from the CCharPPI server were evaluated for this task using decoy structures generated with SwarmDock. Here, we extend this analysis to identify the predictive success rates of the scoring functions on decoys from three rigid‐body docking programs, ZDOCK, FTDock, and SDOCK, allowing us to assess the transferability of the functions. We also apply set‐theoretic measure to test whether the scoring functions are capable of identifying near‐native poses within different subsets of the benchmark. This information can provide guides for the use of the most efficient scoring function for each docking method, as well as instruct future scoring functions development efforts. Proteins 2017; 85:1287–1297. © 2017 Wiley Periodicals, Inc.     

烟草镉的富集及防控措施研究进展

烟草是富镉耐镉作物,降低烟叶镉含量对人体健康十分重要。从烟草镉含量、烟草镉富集及其影响因素、烟草镉防控措施三方面进行了综述,系统分析了该研究领域的成果、现状和存在问题,并对未来烟叶控镉的工作方向进行了展望,以期为低镉烟叶生产提供参考。