Impacts of consumer–resource interaction transitions on persistence and long‐term interaction outcomes of random ecological networks

Despite the prevalence of context‐dependent interaction transitions in ecological systems, their impacts on persistence and interaction diversity have scarcely been explored in complex ecological networks. By using multispecies bi‐directional and unidirectional consumer–resource models, representing a continuum of interaction transitions (sign change of interaction outcomes), we investigated the effects of structural interaction transitions on persistence (the fraction of remaining species) and long‐term interaction outcomes in random ecological networks. We found that high interaction strength of exploiting resources generally decreased persistence, and high strength of providing resources increased persistence when the strength of exploiting resources was low in more complex networks; also, the networks with high persistence had a high proportion of mutualistic interactions relative to antagonistic interactions present initially and over the long term. The shifting of interaction strengths shaped the long‐term interaction compositions. Meanwhile, population dynamics, especially species extinction, affected the difference between initial and long‐term interactions. Based on classical consumer–resource theory, these results establish a transitional continuum of interaction outcomes in ecological networks and imply a theoretical association among interaction transition, community persistence and interaction diversity.     

Evaluating Chemical Interaction Studies for Mixture Risk Assessment

We describe a set of criteria to evaluate the quality of data and interpretations in chemical interaction studies. These criteria reflect the consensus of the literature on interaction analysis developed over decades of research in pharmacology, toxicology, and biometry; address common pitfalls in published interaction studies; and can be easily applied to common methods of interaction analysis. The criteria apply broadly to interaction data for drugs, pesticides, industrial chemicals, food additives, and natural products and are intended to assist risk assessors who must evaluate interaction studies for use in component-based mixture risk assessments. The criteria may also assist researchers interested in conducting interaction studies to inform mixture risk assessment. The criteria are also intended to serve larger scientific goals, including increasing the repeatability of results obtained in chemical interaction studies, enhancing the reliability of conclusions drawn from interaction data, providing greater consistency of interpretations among various analysts, and decreasing uncertainty in using interaction data in risk assessments. We describe the basis for each criterion and demonstrate their utility by using them to evaluate interaction studies from the recent toxicological and pharmacological literature, which serve as examples of different types of data sets that the risk assessor may encounter.     

On the rate of convergence in topology preserving neural networks

A formal analysis of the neighborhood interaction function selection in the topology preserving unsupervised neural network is presented in this paper. The definition of the neighborhood interaction function is motivated by anatomical evidence as opposed to what is currently used, which is a uniform neighborhood interaction set. By selecting a neighborhood interaction function with a neighborhood amplitude of interaction which is decreasing in spatial domain the topological order is always enforced and the rate of self-organization to final equilibrium state is improved. Several simulations are carried out to show the improvement in rate between using a neighborhood interaction function vs. using a neighborhood interaction set. An error measure functional is further defined to compare the two approaches quantitatively.     

Interaction Parameters and the Demise of Paleo-Indian Craftsmanship

Abstract

Interaction plays a central role in archaeological interpretations, yet it has remained theoretically underdeveloped and has often been misused. A framework for dealing with interaction is presented, consisting of: 1) ultimate adaptive conditions for interaction; 2) specific reasons for various types of interaction; 3) modifications of interaction due to aspects of the social matrix; 4) interaction mechanisms; and 5) the artifact patterns resulting from all of these factors. It is clear that “interaction” cannot be treated as a monolithic phenomenon; rather there are many types of interaction with many different outcomes for artifact patterning. The transition from the Paleo-Indian to Archaic stages is analyzed within this framework, and it is suggested that in the simplified interaction context of generalized hunter/ gatherers the size of interaction networks is largely a function of resource reliability and the relative need to maintain subsistence-related alliances between bands.     

PRASA: An integrated web server that analyzes protein interaction types

This work presents the Protein Association Analyzer (PRASA) (http://zoro.ee.ncku.edu.tw/prasa/) that predicts protein interactions as well as interaction types. Protein interactions are essential to most biological functions. The existence of diverse interaction types, such as physically contacted or functionally related interactions, makes protein interactions complex. Different interaction types are distinct and should not be confused. However, most existing tools focus on a specific interaction type or mix different interaction types. This work collected 7234058 associations with experimentally verified interaction types from five databases and compiled individual probabilistic models for different interaction types. The PRASA result page shows predicted associations and their related references by interaction type. Experimental results demonstrate the performance difference when distinguishing between different interaction types. The PRASA provides a centralized and organized platform for easy browsing, downloading and comparing of interaction types, which helps reveal insights into the complex roles that proteins play in organisms.     

Specificity of molecular interactions in transient protein-protein interaction interfaces

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of antibody-antigen complexes, the sign is somewhat ambiguous. From the evolutionary perspective, while protease-inhibitors and sig-naling proteins have optimized their interfaces to suit their biological functions, antibody-antigen interactions are the happenstance, implying that antibody-antigen complexes do not show distinctive interaction types. Persistent interaction types such as pi...pi, amide-carbonyl, and hydroxyl-carbonyl interaction, are also investigated. Analyzing the structural orientations of the pi...pi stacking interactions, we find that herringbone shape is a major configuration in transient protein-protein interfaces. This result is different from that of protein core, where parallel-displaced configurations are the major configuration. We also analyze overall trend of amide-carbonyl and hydroxyl-carbonyl interactions. It is noticeable that nearly 82% of the interfaces have at least one hydroxyl-carbonyl interactions.     

Investigation of the nature of the methionine-pi interaction in beta-hairpin peptide model systems

There are frequent contacts between aromatic rings and sulfur atoms in proteins. However, it is unclear to what degree this putative interaction is stabilizing and what the nature of the interaction is. We have investigated the aryl-sulfur interaction by placing a methionine residue diagonal to an aromatic ring on the same face of a beta-hairpin, which places the methionine side chain in close proximity to the aryl side chain. The methionine (Met)-aryl interaction was compared with an equivalent hydrophobic and cation-pi interaction in the context of the beta-hairpin. The interaction between phenylalanine (Phe), tryptophan (Trp), or cyclohexylalanine (Cha) and Met stabilized the beta-hairpin by -0.3 to -0.5 kcal mole(-1), as determined by double-mutant cycles. The peptides were subjected to thermal denaturations that suggest a hydrophobic driving force for the interactions between Met and Trp or Cha. The observed interaction of Met or norleucine (Nle) with Trp or Cha are quite similar, implying a hydrophobic driving force for the Met-pi interaction. However, the thermodynamic data suggest that there may be some differences between the interaction of Met with Trp and Phe and that there may be a small thermodynamic component to the Met...Phe interaction.     

Small molecules that target phosphorylation dependent protein–protein interaction

Protein–protein interaction is one of the key events in the signal transduction pathway. The interaction changes the conformations, activities, localization and stabilities of the proteins, and transduces the signal to the next step. Frequently, this interaction occurs upon the protein phosphorylation. When upstream signals are stimulated, protein kinase(s) is/are activated and phosphorylate(s) their substrates, and induce the phosphorylation dependent protein–protein interaction. For this interaction, several domains in proteins are known to specifically recognize the phosphorylated residues of target proteins. These specific domains for interaction are important in the progression of the diseases caused by disordered signal transduction such as cancer. Thus small molecules that modulate this interaction are attractive lead compounds for the treatment of such diseases. In this review, we focused on three examples of phosphorylation dependent protein–protein interaction modules (14-3-3, polo box domain of Plk1 and F-box proteins in SCF ubiquitin ligases) and summarize small molecules that modulate their interaction. We also introduce our original screening system to identify such small molecules.     

温度和时间对肌红蛋白血红素铁与金属离子相互作用的影响

目的:研究在生理条件下,温度和时间对肌红蛋白血红素铁与各种金属离子直接相互作用的影响。方法:利用紫外-可见光谱法研究肌红蛋白活性中心的铁和外加金属离子(CuSO4、ZnSO4、MgSO4、CoCl2和MnSO4)的直接相互作用;改变作用温度(4、21、37和52℃)和作用时间(2、4、6、8和10 d),研究肌红蛋白活性中心铁卟啉与不同金属离子的直接相互作用。结果与结论:紫外光谱数据表明,金属离子与肌红蛋白活性中心的Fe(Ⅱ)发生直接相互作用,且随着作用温度的升高和作用时间的延长,这种相互作用逐渐增强。作用10 d后,金属离子与肌红蛋白活性中心的铁的作用强度依次为Mn(Ⅱ)>Zn(Ⅱ)>Co(Ⅱ);温度升至52℃时,作用强度依次为Cu(Ⅱ)>Mg(Ⅱ)>Zn(Ⅱ)。     

人类蛋白质相互作用组

高通量酵母双杂交与免疫亲和纯化技术的快速发展和日臻成熟,使得在蛋白质组水平上大规模地研究蛋白质之间的相互作用成为可能。目前,人类蛋白质互作网络在细胞、组织、器官乃至整个个体水平的研究已经陆续展开。蛋白质互作网络中蛋白质数量也由少数几个向整个蛋白质组扩展。同时,功能、疾病、生态等相关的蛋白质互作网络研究也取得了一定的成果。然而,人类的蛋白质互作网络研究正面临着一些问题和挑战。本文综述了人类蛋白质互作网络的研究方法、研究进展以及面临的挑战,同时指出了人类蛋白质互作网络研究的方向和目标。     

Standardization and application of metrics to quantify human‐interaction behaviors by the bottlenose dolphin (Tursiops spp.)

The conditioning of dolphins to human‐interaction behaviors has been documented in several areas worldwide. However, the metrics used to report human‐interaction behaviors vary among studies, making comparison across study areas difficult. The purpose of this study was to develop standard metrics for reporting human‐interaction behaviors and utilize these metrics to quantify the prevalence of human‐interaction behaviors by common bottlenose dolphins (Tursiops truncatus) near Savannah, Georgia. The four metrics used were percentage of days with human‐interaction behaviors, percentage of sightings with human‐interaction behaviors, percentage of the catalog that interacted with humans, and spatial extent of human‐interaction behaviors. Human‐interaction behaviors were observed on 69.6% of days and 23.5% of sightings near Savannah. In addition, 20.1% of the animals in the catalog were observed interacting with humans. These rates are much higher than those found in other areas with known issues with human‐interaction behaviors. These behaviors were observed across an area of 272.6 km², which is larger than other reported areas. The four metrics used in this study proved to be a valuable way to report human‐interaction behaviors, and their use is recommended for future studies to allow for comparison among areas.     

大规模酵母双杂交技术研究蛋白质相互作用的应用

简介了酵母双杂交技术原理, 总结了酵母双杂交技术大规模筛选蛋白质相互作用的基础、应用及存在的问题。因为大规模酵母双杂交技术结果有大量假阳性及假阴性问题, 因此, 有条件情况下有必要同时开展其他方法的大规模蛋白相互作用研究, 以构建规模更大可信度更高的蛋白质相互作用网络图。     

Type IV secretion system core component VirB8 from Brucella binds to the globular domain of VirB5 and to a periplasmic domain of VirB6

Type IV secretion systems are macromolecular assemblies in the cell envelopes of bacteria that function in macromolecular translocation. Structural biology approaches have provided insights into the interaction of core complex components, but information about proteins that undergo transient interactions with membrane components has not been forthcoming. We have pursued an unbiased approach using peptide arrays and phage display to identify interaction partners and interaction domains of type IV secretion system assembly factor VirB8. These approaches identified the globular domain from the VirB5 protein to interact with VirB8. This interaction was confirmed in cross-linking, pull-down, and fluorescence resonance energy transfer (FRET)-based interaction assays. In addition, using phage display analysis, we identified different regions of VirB6 as potential interaction partners of VirB8. Using a FRET-based interaction assay, we provide the first direct experimental evidence of the interaction of a VirB6 periplasmic domain with VirB8. These results will allow us to conduct directed structural biological work and structure-function analyses aimed at defining the molecular details and biological significance of these interactions with VirB8 in the future.     

Virus-specific interaction between the human cytomegalovirus major capsid protein and the C terminus of the assembly protein precursor.

We previously identified a minimal 12-amino-acid domain in the C terminus of the herpes simplex virus type 1 (HSV-1) scaffolding protein which is required for interaction with the HSV-1 major capsid protein. An alpha-helical structure which maximizes the hydropathicity of the minimal domain is required for the interaction. To address whether cytomegalovirus (CMV) utilizes the same strategy for capsid assembly, several glutathione S-transferase fusion proteins to the C terminus of the CMV assembly protein precursor were produced and purified from bacterial cells. The study showed that the glutathione S-transferase fusion containing 16 amino acids near the C-terminal end was sufficient to interact with the major capsid protein. Interestingly, no cross-interaction between HSV-1 and CMV could be detected. Mutation analysis revealed that a three-amino-acid region at the N-terminal side of the central Phe residue of the CMV interaction domain played a role in determining the viral specificity of the interaction. When this region was converted so as to correspond to that of HSV-1, the CMV assembly protein domain lost its ability to interact with the CMV major capsid protein but gained full interaction with the HSV-1 major capsid protein. To address whether the minimal interaction domain of the CMV assembly protein forms an alpha-helical structure similar to that in HSV-1, peptide competition experiments were carried out. The results showed that a cyclic peptide derived from the interaction domain with a constrained (alpha-helical structure competed for interaction with the major capsid protein much more efficiently than the unconstrained linear peptide. In contrast, a cyclic peptide containing an Ala substitution for the critical Phe residue did not compete for the interaction at all. The results of this study suggest that (i) CMV may have developed a strategy similar to that of HSV-1 for capsid assembly; (ii) the minimal interaction motif in the CMV assembly protein requires an alpha-helix for efficient interaction with the major capsid protein; and (iii) the Phe residue in the CMV minimal interaction domain is critical for interaction with the major capsid protein.     

Network evolution: rewiring and signatures of conservation in signaling

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.     

Red blood cell aggregation and dissociation in shear flows simulated by lattice Boltzmann method

In this paper we develop a lattice Boltzmann algorithm to simulate red blood cell (RBC) behavior in shear flows. The immersed boundary method is employed to incorporate the fluid-membrane interaction between the flow field and deformable cells. The cell membrane is treated as a neo-Hookean viscoelastic material and a Morse potential is adopted to model the intercellular interaction. Utilizing the available mechanical properties of RBCs, multiple cells have been studied in shear flows using a two-dimensional approximation. These cells aggregate and form a rouleau under the action of intercellular interaction. The equilibrium configuration is related to the interaction strength. The end cells exhibit concave shapes under weak interaction and convex shapes under strong interaction. In shear flows, such a rouleau-like aggregate will rotate or be separated, depending on the relative strengths of the intercellular interaction and hydrodynamic viscous forces. These behaviors are qualitatively similar to experimental observations and show the potential of this numerical scheme for future studies of blood flow in microvessels.     

Thioredoxin-dependent regulation of AIF-mediated DNA damage

The thioredoxin (Trx) system is one major redox system in mammalian cells. One of its component, Trx, is involved in redox homeostasis and many cellular biological processes through participating in disulfide reduction, S-nitrosylation/S-denitrosylation reactions and protein-protein interactions. In this study, we report the identification of a novel interaction between cytosolic/nuclear Trx1 and apoptosis inducing factor (AIF), and the redox sensitivity and biological significance of the Trx-AIF interaction was characterized. Cytosolic Trx1 but not mitochondrial Trx2 was observed to interact with AIF under physiological conditions and Trx1's active site cysteines were crucial for the interaction. Under oxidative stress conditions, Trx-AIF interaction was disrupted. When the treated cells were allowed to recover from oxidative stress by means of removal of the oxidants, interaction between Trx1 and AIF was re-established time-dependently, which underpins the biological relevance of a Trx-dependent redox regulation of AIF-mediated cell death. Indeed, in times of oxidative stress, nuclear translocation of AIF was found to occur concurrently with perturbations to the Trx-AIF interaction. Once localized in the nucleus, reduced Trx1 hindered the interaction between AIF and DNA, thereby bringing about an attenuation of AIF-mediated DNA damage. In conclusion, characterization of the Trx-AIF interaction has led to an understanding of the effect of reduced Trx1 on possibly regulating AIF-dependent cell death through impeding AIF-mediated DNA damage. Importantly, identification of the novel interaction between Trx1 and AIF has provided opportunities to design and develop therapeutically relevant strategies that either promote or prevent this protein-protein interaction for the treatment of different disease states.     

Inferring mechanisms of compensation from E-MAP and SGA data using local search algorithms for max cut

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.     

Direct interaction between emerin and lamin A

Emerin is the protein of the inner nuclear membrane that is affected by mutation in X-linked Emery-Dreifuss muscular dystrophy. The autosomal dominant form of the disease is caused by mutations in the lamin A/C gene. Several lines of circumstantial evidence have suggested an interaction of emerin with lamins in the nuclear lamina but direct interaction between the two proteins has not yet been demonstrated. We now demonstrate direct interaction between recombinant emerin and lamin A molecules using biomolecular interaction analysis (BIA) and monoclonal antibodies. An emerin-lamin A interaction system may be related in function to the LAP2-lamin B system at the inner nuclear rim.