北方农牧交错带沽源农田-草地界面土壤水热空间特征

农田-草地景观界面是我国北方农牧交错带景观组成部分,研究该界面生态特征的格局和过程是完善北方农牧交错带研究的热点领域.首次采用地统计学方法中的半变异函数、克里格插值估计、空间分布图等方法研究北方农牧交错带河北沽源地区的农田-草地界面(CGB)土壤水热的空间异质性和界面空间效应.结果表明:根据不同尺度下的土壤水热空间异质性各参数的变化趋势确定较为合理的采样粒度为 0.5m×0.5m;农田-草地界面0～20cm土层土壤含水量为中等变异,土壤温度为弱变异,不同采样粒度空间结构特征定量研究得到土壤水分变程范围(A_0)为2.93～15.4m,且为中到强度的异质性程度(MSH),土壤温度变程为3.75～20.99m,表现为强空间异质性;验证在农田-草地边界向两侧的一定范围内土壤水热存在过渡型界面效应,且具不同的生态梯度.该研究结果是认识农田-草地界面和进一步开展该界面功能研究的基础,对深入研究北方农牧交错带农田-草地界面非生物水热界面具有重要意义.     

农林生态系统界面生态学初探

对界面生态 的概念、界面生态学的主要研究内容?界面生态学在农林复合生态系统中的应用进行了系统的论述,农林复合生态系统中树木对农作物的作用机制主要体现在以空气为介质的光、热、水分竞争的地上界面和以土壤为介质的养分、水分竞争的地下界面上,界面上物质、能量、信息的交换和传递反映了农林复合生态系统中树林和农作物的作用机理。     

铜绿假单胞菌在液滴界面的二维和三维运动特征

【目的】环境中无处不在的气-液界面能够影响细菌的运动和养分的传输扩散,进而调控微生物的种群互作和群落结构。因此,系统地认知微生物在微观界面的运动特征对于理解和解析微生物多样性的产生、维持机制以及生态功能至关重要。【方法】本文基于微流体显微系统(超高速荧光显微镜和数字全息显微镜),以具备主动运动能力的模式菌株铜绿假单胞菌(Pseudomonas aeruginosaPAO1)为研究对象,观测并解析了细菌细胞在气-液界面的二维运动特征和气-液-固界面的二维与三维运动特征。【结果】PAO1既能在气-液界面处执行近似直线轨迹的运动,也能在气-液界面下方执行顺时针或逆时针旋转的圆周运动(最小曲率半径Rmin=3μm)。在气-液-固界面处,6.45%的不运动细胞聚集于气-液-固界面边缘处,并在该处完成不可逆附着;同时,游动细胞由于受到液滴内部毛细管流和马兰戈尼(Marangoni)涡流运动的综合作用,直线游动至距界面约40μm内的区域后,其运动轨迹转变为垂直界面方向返回或以近似界面平行方向运动并附着,这些行为显著调节了PAO1的空间分布,促使了其朝向气-液-固界面的迁移,表明个体PAO1的鞭毛在此...     

沉水植物茎叶微界面特性研究进展

沉水植物茎叶-水界面是浅水湖泊的重要界面之一,对湖泊生物地球化学循环和水环境质量具有重要影响。富营养化水体中,大量的附着物常富集在沉水植物茎叶表面,形成了特殊的生物-水微界面。对该微界面特性进行深入研究,有助于揭示沉水植物在微环境层面对富营养化水体中物质循环的调控过程和机制。沉水植物茎叶微界面具有促进水体养分转化、改变环境因子及可溶性物质的空间分布,增加物质运输的阻力和距离、降低植物光合作用、调控重金属等生态功能;微界面结构及环境因子受水体营养盐浓度、沉水植物种类及生长阶段等因素的影响。对微界面结构功能的主要研究方法进行了分析总结,并对沉水植物茎叶微界面的研究前沿进行了展望。     

贵州喀斯特山区人工草地-农田景观土壤温度界面季节性变化

景观界面是生态交错区的重要组成部分,在生态系统的结构、过程和功能中发挥了重要的作用。以贵州喀斯特山区人工草地-农田景观界面为研究对象,对界面表层土壤(0—20 cm)温度进行季节性监测;采用移动窗口法、野外测定和室内统计相结合,对以土壤温度为参数的界面宽度的大小进行了判定;对研究区3个功能区土壤温度进行比较分析。结果表明:贵州人工草地-农田景观界面四季表层土壤的平均温度分别为9.8,26.5,15.4℃和4.8℃;人工草地-农田景观春、夏、秋、冬四季土壤温度界面宽度随土壤温度的变化而变化,表现为由宽变窄的变化规律,分别为37,32,27 m和24 m,土壤温度界面在人工草地系统的影响域变化与总界面宽度保持一致。研究区四季农田功能区系统、人工草地-农田复合功能区系统和人工草地功能区系统的平均土壤温度为14.0,14.1℃和13.9℃,春季、夏季和冬季研究区3个功能区的土壤温度均呈极显著差异,秋季农田功能区系统与人工草地-农田复合功能区系统的土壤温度差异不显著,二者与草地功能区系统差异极显著。建议对研究区采用12—18 m的宽度进行草田间作,为丰富界面理论及"退耕还草"工程提供理论参考和实践措施。     

景观生态界面边界判定与动态模拟研究进展

栖息地边界对景观结构和功能具深远影响,既影响局部又作用于更大尺度区域的生态过程,同时界面的动态特征通过反馈机制影响着不同种群、群落以及生态系统。因此,在景观生态界面研究中,界面尺度依赖性和时空动态性的定量化研究已成为模型和统计学者的研究热点。鉴于此,通过介绍生态界面描述、界面监测及相关边界动态变化特征研究,阐述统计学和数学方法在不同生态系统、生态过程及尺度下界面研究中的应用,同时指出两者结合研究在生态界面定量的研究中仍面临着概念和方法上的挑战,为进一步提高景观生态界面综合研究水平提供参考。     

阿尔茨海默病中的β-淀粉样蛋白和Tau蛋白

阿尔茨海默病(Alzheimer’s disease,AD)是与年龄相关的神经退行性疾病。记忆障碍通常是AD最早期和最明显的特征。β-淀粉样蛋白(amyloid-β,Aβ)沉淀(老年斑)、Tau蛋白引起的神经纤维缠结是AD的典型病理特征。许多研究证实两者之间存在着极为复杂的互为因果关系,共同造成神经元的损害。     

微生物-矿物相互作用及界面显微分析研究进展

微生物-矿物界面的相互作用贯穿着整个生物浸矿过程,在矿物生物浸出中至关重要,受到微生物的代谢特征、矿物表面结构和物质形态及环境条件的多重交叉影响。研究微生物-矿物界面的相互作用相关的微生物选择性吸附、矿物表面元素形态转化和钝化层、微生物铁硫氧化活性和微生物群落以及胞外物质的组成和性质等的演化,有利于了解微生物-矿物界面作用机制及其关键影响因素和影响机制,从而为优化浸出工艺提供科学的理论依据。达到这些目的,界面的(原位)显微分析手段和技术的进步也至关重要。本文对近些年来上述两方面的研究进行了综述。     

沉水植物茎叶微界面及其对水体氮循环影响研究进展

沉水植物茎叶表面常富集了水中各类物质,包括有机质、泥沙、菌胶团、藻类、微生物等,形成厚度不等的附着层,形成特殊的茎叶微界面,其具有特殊的氧化-还原异质环境,并能为氮素循环细菌提供有机质,是水中氨化、反硝化及厌氧氨氧化等脱氮行为的重要基础,因此,了解沉水植物茎叶微界面组分、微环境变化特征及其对氮循环的调控作用,对于正确认识和利用沉水植物的生态调控功能、改善水环境质量具有十分重要的意义。基于此,就沉水植物茎叶微界面物质组成、微环境特征及其对水体氮循环影响研究现状进行了归纳总结,并对今后的研究方向进行了简要展望。     

蛋白质-蛋白质界面热点残基预测及其在线工具

蛋白质-蛋白质结合热点是界面中对结合自由能有着显著贡献的一小簇残基。捕捉和揭示这类热点残基可以加深对蛋白质间相互作用机制的理解,为蛋白质工程和药物设计提供指导。但实验技术费时费力且代价昂贵。计算工具可用于辅助和补充实验上的尝试。该文较详细、系统地介绍了蛋白质界面热点的特性、计算预测的策略与技术,并应用实例进一步说明这些方法学的特征;还介绍了界面热点的数据库和一些主要的在线预测工具,旨在为设计、挑选和应用这类工具解决特定问题的研究人员提供指南。     

A new, structurally nonredundant, diverse data set of protein-protein interfaces and its implications

Here, we present a diverse, structurally nonredundant data set of two-chain protein-protein interfaces derived from the PDB. Using a sequence order-independent structural comparison algorithm and hierarchical clustering, 3799 interface clusters are obtained. These yield 103 clusters with at least five nonhomologous members. We divide the clusters into three types. In Type I clusters, the global structures of the chains from which the interfaces are derived are also similar. This cluster type is expected because, in general, related proteins associate in similar ways. In Type II, the interfaces are similar; however, remarkably, the overall structures and functions of the chains are different. The functional spectrum is broad, from enzymes/inhibitors to immunoglobulins and toxins. The fact that structurally different monomers associate in similar ways, suggests "good" binding architectures. This observation extends a paradigm in protein science: It has been well known that proteins with similar structures may have different functions. Here, we show that it extends to interfaces. In Type III clusters, only one side of the interface is similar across the cluster. This structurally nonredundant data set provides rich data for studies of protein-protein interactions and recognition, cellular networks and drug design. In particular, it may be useful in addressing the difficult question of what are the favorable ways for proteins to interact. (The data set is available at http://protein3d.ncifcrf.gov/~keskino/ and http://home.ku.edu.tr/~okeskin/INTERFACE/INTERFACES.html.)     

Studies of protein-protein interfaces: a statistical analysis of the hydrophobic effect.

Data sets of 362 structurally nonredundant protein-protein interfaces and of 57 symmetry-related oligomeric interfaces have been used to explore whether the hydrophobic effect that guides protein folding is also the main driving force for protein-protein associations. The buried nonpolar surface area has been used to measure the hydrophobic effect. Our analysis indicates that, although the hydrophobic effect plays a dominant role in protein-protein binding, it is not as strong as that observed in the interior of protein monomers. Comparison of interiors of the monomers with those of the interfaces reveals that, in general, the hydrophobic amino acids are more frequent in the interior of the monomers than in the interior of the protein-protein interfaces. On the other hand, a higher proportion of charged and polar residues are buried at the interfaces, suggesting that hydrogen bonds and ion pairs contribute more to the stability of protein binding than to that of protein folding. Moreover, comparison of the interior of the interfaces to protein surfaces indicates that the interfaces are poorer in polar/charged than the surfaces and are richer in hydrophobic residues. The interior of the interfaces appears to constitute a compromise between the stabilization contributed by the hydrophobic effect on the one hand and avoiding patches on the protein surfaces that are too hydrophobic on the other. Such patches would be unfavorable for the unassociated monomers in solution. We conclude that, although the types of interactions are similar between protein-protein interfaces and single-chain proteins overall, the contribution of the hydrophobic effect to protein-protein associations is not as strong as to protein folding. This implies that packing patterns and interatom, or interresidue, pairwise potential functions, derived from monomers, are not ideally suited to predicting and assessing ligand associations or design. These would perform adequately only in cases where the hydrophobic effect at the binding site is substantial.     

Generation and analysis of a protein-protein interface data set with similar chemical and spatial patterns of interactions

Protein-protein interfaces are regions between 2 polypeptide chains that are not covalently connected. Here, we have created a nonredundant interface data set generated from all 2-chain interfaces in the Protein Data Bank. This data set is unique, since it contains clusters of interfaces with similar shapes and spatial organization of chemical functional groups. The data set allows statistical investigation of similar interfaces, as well as the identification and analysis of the chemical forces that account for the protein-protein associations. Toward this goal, we have developed I2I-SiteEngine (Interface-to-Interface SiteEngine) [Data set available at http://bioinfo3d.cs.tau.ac.il/Interfaces; Web server: http://bioinfo3d.cs.tau.ac.il/I2I-SiteEngine]. The algorithm recognizes similarities between protein-protein binding surfaces. I2I-SiteEngine is independent of the sequence or the fold of the proteins that comprise the interfaces. In addition to geometry, the method takes into account both the backbone and the side-chain physicochemical properties of the interacting atom groups. Its high efficiency makes it suitable for large-scale database searches and classifications. Below, we briefly describe the I2I-SiteEngine method. We focus on the classification process and the obtained nonredundant protein-protein interface data set. In particular, we analyze the biological significance of the clusters and present examples which illustrate that given constellations of chemical groups in protein-protein binding sites may be preferred, and are observed in proteins with different structures and different functions. We expect that these would yield further information regarding the forces stabilizing protein-protein interactions.     

Amino acid substitutions at protein–protein interfaces that modulate the oligomeric state

Despite similarities in their sequence and structure, there are a number of homologous proteins that adopt various oligomeric states. Comparisons of these homologous protein pairs, in terms of residue substitutions at the protein–protein interfaces, have provided fundamental characteristics that describe how proteins interact with each other. We have prepared a dataset composed of pairs of related proteins with different homo‐oligomeric states. Using the protein complexes, the interface residues were identified, and using structural alignments, the shadow‐interface residues have been defined as the surface residues that align with the interface residues. Subsequently, we investigated residue substitutions between the interfaces and the shadow interfaces. Based on the degree of the contributions to the interactions, the aligned sites of the interfaces and shadow interfaces were divided into primary and secondary sites; the primary sites are the focus of this work. The primary sites were further classified into two groups (i.e. exposed and buried) based on the degree to which the residue is buried within the shadow interfaces. Using these classifications, two simple mechanisms that mediate the oligomeric states were identified. In the primary‐exposed sites, the residues on the shadow interfaces are replaced by more hydrophobic or aromatic residues, which are physicochemically favored at protein–protein interfaces. In the primary‐buried sites, the residues on the shadow interfaces are replaced by larger residues that protrude into other proteins. These simple rules are satisfied in 23 out of 25 Structural Classification of Proteins (SCOP) families with a different‐oligomeric‐state pair, and thus represent a basic strategy for modulating protein associations and dissociations. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Characterization of Protein–Protein Interfaces

We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.     

Back Cover Image,Volume 117, Number 2, February 2020

During the manufacturing process, solutions of protein-based drugs are exposed to hydrodynamic forces, which can potentially affect protein stability and aggregation. Despite being an area of extensive investigation, the effect of hydrodynamic flow on protein aggregation is still controversial. In this study, we designed an experimental setup that allowed us to investigate flow- and interface-induced protein aggregation of two model immunoglobulins in the presence of well-defined flow stresses and solid–liquid interfaces. Within the range of shear rates typically encountered in bioprocessing (), we observed that increasing the shear rate by three orders of magnitude had a negligible effect on protein aggregation. By contrast, changes in the materials of the syringe barrels had a dramatic effect on the monomer loss, demonstrating the key role of solid–liquid interfaces in flow-induced aggregation. This finding was confirmed by the observed inverse dependence of the aggregation rate on the initial protein concentration, which is inconsistent with mechanisms of protein aggregation in bulk solution. Overall, our results reveal the presence of a synergistic effect of interfaces and hydrodynamic flow in flow-induced protein aggregation, which arises from the formation of protein particles or films on interfaces followed by displacement by flow or mechanical scraping.     

Weak conservation of structural features in the interfaces of homologous transient protein–protein complexes

Residue types at the interface of protein–protein complexes (PPCs) are known to be reasonably well conserved. However, we show, using a dataset of known 3‐D structures of homologous transient PPCs, that the 3‐D location of interfacial residues and their interaction patterns are only moderately and poorly conserved, respectively. Another surprising observation is that a residue at the interface that is conserved is not necessarily in the interface in the homolog. Such differences in homologous complexes are manifested by substitution of the residues that are spatially proximal to the conserved residue and structural differences at the interfaces as well as differences in spatial orientations of the interacting proteins. Conservation of interface location and the interaction pattern at the core of the interfaces is higher than at the periphery of the interface patch. Extents of variability of various structural features reported here for homologous transient PPCs are higher than the variation in homologous permanent homomers. Our findings suggest that straightforward extrapolation of interfacial nature and inter‐residue interaction patterns from template to target could lead to serious errors in the modeled complex structure. Understanding the evolution of interfaces provides insights to improve comparative modeling of PPC structures.     

Dynamic features of homodimer interfaces calculated by normal‐mode analysis

Knowledge of the dynamic features of protein interfaces is necessary for a deeper understanding of protein–protein interactions. We performed normal‐mode analysis (NMA) of 517 nonredundant homodimers and their protomers to characterize dimer interfaces from a dynamic perspective. The motion vector calculated by NMA for each atom of a dimer was decomposed into internal and external motion vectors in individual component subunits, followed by the averaging of time‐averaged correlations between these vectors over atom pairs in the interface. This averaged correlation coefficient (ACC) was defined for various combinations of vectors and investigated in detail. ACCs decrease exponentially with an increasing interface area and r‐value, that is, interface area divided by the entire subunit surface area. As the r‐value reflects the nature of dimer formation, the result suggests that both the interface area and the nature of dimer formation are responsible for the dynamic properties of dimer interfaces. For interfaces with small or medium r‐values and without intersubunit entanglements, ACCs are found to increase on dimer formation when compared with those in the protomer state. In contrast, ACCs do not increase on dimer formation for interfaces with large r‐values and intersubunit entanglements such as in interwinding dimers. Furthermore, relationships between ACCs for intrasubunit atom pairs and for intersubunit atom pairs are found to significantly differ between interwinding and noninterwinding dimers for external motions. External motions are considered as an important factor for characterizing dimer interfaces.     

Dissecting protein‐protein interactions in proteasome assembly: Implication to its self‐assembly

The 26S proteasome is a multi‐catalytic ATP‐dependent protease complex that recognizes and cleaves damaged or misfolded proteins to maintain cellular homeostasis. The 26S subunit consists of 20S core and 19S regulatory particles. 20S core particle consists of a stack of heptameric alpha and beta subunits. To elucidate the structure‐function relationship, we have dissected protein‐protein interfaces of 20S core particle and analyzed structural and physiochemical properties of intra‐alpha, intra‐beta, inter‐beta, and alpha‐beta interfaces. Furthermore, we have studied the evolutionary conservation of 20S core particle. We find the size of intra‐alpha interfaces is significantly larger and is more hydrophobic compared with other interfaces. Inter‐beta interfaces are well packed, more polar, and have higher salt‐bridge density than other interfaces. In proteasome assembly, residues in beta subunits are better conserved than alpha subunits, while multi‐interface residues are the most conserved. Among all the residues at the interfaces of both alpha and beta subunits, Gly is highly conserved. The largest size of intra‐alpha interfaces complies with the hypothesis that large interfaces form first during the 20S assembly. The tight packing of inter‐beta interfaces makes the core particle impenetrable from outer wall of the cylinder. Comparing the three domains, eukaryotes have large and well‐packed interfaces followed by archaea and bacteria. Our findings provide a structural basis of assembly of 20S core particle in all the three domains of life.