An information-theoretic approach to interactions in images.

In this paper it will be argued that the notion of interactions in images is closely related to that of entropy associated with an image, and it will be shown that interactions make processing of the information coming from the retina computationally less expensive. A procedure will be presented, based on the evolution of joint entropy across different scales, to gauge the contributions of different types of interactions to the structure of the images.     

Predicting novel RNA-RNA interactions

The purpose of this article is to give a brief, yet concise overview of the current computational methods for predicting novel RNA-RNA interactions, that is interactions whose characteristic features we do not yet know. We start by briefly reviewing experimentally confirmed examples of RNA-RNA interactions before introducing computational methods for predicting RNA-RNA interactions. We will focus primarily on the interactions between different RNA molecules, that is trans RNA-RNA interactions, and will only discuss methods for predicting RNA structure, that is cis-only RNA-RNA interactions, where this helps to gain a better understanding. We conclude by discussing the merits of the different approaches and provide an outlook on probably and desirable future developments in the field.     

Species interactions and climate change: How the disruption of species co‐occurrence will impact on an avian forest guild

Interspecific interactions are crucial in determining species occurrence and community assembly. Understanding these interactions is thus essential for correctly predicting species' responses to climate change. We focussed on an avian forest guild of four hole‐nesting species with differing sensitivities to climate that show a range of well‐understood reciprocal interactions, including facilitation, competition and predation. We modelled the potential distributions of black woodpecker and boreal, tawny and Ural owl, and tested whether the spatial patterns of the more widespread species (excluding Ural owl) were shaped by interspecific interactions. We then modelled the potential future distributions of all four species, evaluating how the predicted changes will alter the overlap between the species' ranges, and hence the spatial outcomes of interactions. Forest cover/type and climate were important determinants of habitat suitability for all species. Field data analysed with N‐mixture models revealed effects of interspecific interactions on current species abundance, especially in boreal owl (positive effects of black woodpecker, negative effects of tawny owl). Climate change will impact the assemblage both at species and guild levels, as the potential area of range overlap, relevant for species interactions, will change in both proportion and extent in the future. Boreal owl, the most climate‐sensitive species in the guild, will retreat, and the range overlap with its main predator, tawny owl, will increase in the remaining suitable area: climate change will thus impact on boreal owl both directly and indirectly. Climate change will cause the geographical alteration or disruption of species interaction networks, with different consequences for the species belonging to the guild and a likely spatial increase of competition and/or intraguild predation. Our work shows significant interactions and important potential changes in the overlap of areas suitable for the interacting species, which reinforce the importance of including relevant biotic interactions in predictive climate change models for increasing forecast accuracy.     

Functional protein microarray: an ideal platform for investigating protein binding property

Functional protein microarray is an important tool for high-throughput and large-scale systems biology studies.Besides the progresses that have been made for protein microarray fabrication,significant ...     

Principles of protein-protein interactions

In the postgenomic era, one of the most interesting and important challenges is to understand protein interactions on a large scale. The physical interactions between protein domains are fundamental to the workings of a cell: in multi-domain polypeptide chains, in multi-subunit proteins and in transient complexes between proteins that also exist independently. Thus experimental investigation of protein-protein interactions has been extensive, including recent large-scale screens using mass spectrometry. The role of computational research on protein-protein interactions encompasses not only prediction, but also understanding the nature of the interactions and their three-dimensional structures. I will discuss properties such as sequence conservation and co-regulation of genes and proteins involved in different types of physical interactions. Given that all proteins consist of their evolutionary units, the domains, all interactions occur between these domains. The interactions between domains belonging to different protein families will be the second topic of my talk.     

Social cognitive neuroscience and humanoid robotics

We believe that humanoid robots provide new tools to investigate human social cognition, the processes underlying everyday interactions between individuals. Resonance is an emerging framework to understand social interactions that is based on the finding that cognitive processes involved when experiencing a mental state and when perceiving another individual experiencing the same mental state overlap, both at the behavioral and neural levels. We will first review important aspects of his framework. In a second part, we will discuss how this framework is used to address questions pertaining to artificial agents’ social competence. We will focus on two types of paradigm, one derived from experimental psychology and the other using neuroimaging, that have been used to investigate humans’ responses to humanoid robots. Finally, we will speculate on the consequences of resonance in natural social interactions if humanoid robots are to become integral part of our societies.     

Next-generation sequencing: A new avenue to understand viral RNA–protein interactions

The genomes of RNA viruses present an astonishing source of both sequence and structural diversity. From intracellular viral RNA-host interfaces to interactions between the RNA genome and structural proteins in virus particles themselves, almost the entire viral lifecycle is accompanied by a myriad of RNA–protein interactions that are required to fulfill their replicative potential. It is therefore important to characterize such rich and dynamic collections of viral RNA–protein interactions to understand virus evolution and their adaptation to their hosts and environment. Recent advances in next-generation sequencing technologies have allowed the characterization of viral RNA–protein interactions, including both transient and conserved interactions, where molecular and structural approaches have fallen short. In this review, we will provide a methodological overview of the high-throughput techniques used to study viral RNA–protein interactions, their biochemical mechanisms, and how they evolved from classical methods as well as one another. We will discuss how different techniques have fueled virus research to characterize how viral RNA and proteins interact, both locally and on a global scale. Finally, we will present examples on how these techniques influence the studies of clinically important pathogens such as HIV-1 and SARS-CoV-2.     

Functional aspects of polyisoprenoid protein substituents: roles in protein-protein interaction and trafficking

There are now numerous examples of post-translational modification with geranylgeranyl or farnesyl substituents. Once thought of as solely a mechanism for association of proteins with membranes, other functional aspects of protein prenylation have come to be appreciated. Although, in almost all instances, such proteins are membrane associated, they are often found to also engage in protein-protein interactions. In some instances, such interactions are critical aspects of prenylated protein trafficking. In this review, the role of prenylation in mediating protein-protein interactions will be considered. The hypothesis will be developed that such interactions occur through recognition of the prenyl group and a second domain, on the prenylated protein, by a heterodimeric protein partner.     

Predator–prey interactions and changing environments: who benefits?

While aquatic environments have long been thought to be more moderate environments than their terrestrial cousins, environmental data demonstrate that for some systems this is not so. Numerous important environmental parameters can fluctuate dramatically, notably dissolved oxygen, turbidity and temperature. The roles of dissolved oxygen and turbidity on predator-prey interactions have been discussed in detail elsewhere within this issue and will be considered only briefly here. Here, we will focus primarily on the role of temperature and its potential impact upon predator-prey interactions. Two key properties are of particular note. For temperate aquatic ecosystems, all piscine and invertebrate piscivores and their prey are ectothermic. They will therefore be subject to energetic demands that are significantly affected by environmental temperature. Furthermore, the physical properties of water, particularly its high thermal conductivity, mean that thermal microenvironments will not exist so that fine-scale habitat movements will not be an option for dealing with changing water temperature in lentic environments. Unfortunately, there has been little experimental analysis of the role of temperature on such predator-prey interactions, so we will instead focus on theoretical work, indicating that potential implications associated with thermal change are unlikely to be straightforward and may present a greater threat to predators than to their prey. Specifically, we demonstrate that changes in the thermal environment can result in a net benefit to cold-adapted species through the mechanism of predator-prey interactions.     

发现靶向蛋白质间相互作用的小分子药物研究进展

蛋白质-蛋白质相互作用在多种细胞功能中具有重要的作用。靶向蛋白质-蛋白质相互作用已经成为新药发现的重要策略,但发现能阻断蛋白质-蛋白质相互作用的小分子药物是一个巨大的挑战。尽管如此,近年来人们还是发现了许多能调控蛋白质-蛋白质相互作用的小分子。该文主要总结了在病毒进入、细胞凋亡通路和神经退行性疾病等方面的蛋白质-蛋白质相互作用小分子抑制剂的研究进展。     

Polymicrobial infections involving clinically relevant Gram‐negative bacteria and fungi

Interactions between fungi and bacteria and their relevance to human health and disease have recently attracted increased attention in biomedical fields. Emerging evidence shows that bacteria and fungi can have synergistic or antagonistic interactions, each with important implications for human colonization and disease. It is now appreciated that some of these interactions may be strategic and helps promote the survival of one or both microorganisms within the host. This review will shed light on clinically relevant interactions between fungi and Gram‐negative bacteria. Mechanism of interaction, host immune responses, and preventive measures will also be reviewed.     

Epistasis and the mutation load: a measurement-theoretical approach

An approximate solution for the mean fitness in mutation-selection balance with arbitrary order of epistatic interaction is derived. The solution is based on the assumptions of coupling equilibrium and that the interaction effects are multilinear. We find that the effect of m-order epistatic interactions (i.e., interactions among groups of m loci) on the load is dependent on the total genomic mutation rate, U, to the mth power. Thus, higher-order gene interactions are potentially important if U is large and the interaction density among loci is not too low. The solution suggests that synergistic epistasis will decrease the mutation load and that variation in epistatic effects will elevate the load. Both of these results, however, are strictly true only if they refer to epistatic interaction strengths measured in the optimal genotype. If gene interactions are measured at mutation-selection equilibrium, only synergistic interactions among even numbers of genes will reduce the load. Odd-ordered synergistic interactions will then elevate the load. There is no systematic relationship between variation in epistasis and load at equilibrium. We argue that empirical estimates of gene interaction must pay attention to the genetic background in which the effects are measured and that it may be advantageous to refer to average interaction intensities as measured in mutation-selection equilibrium. We derive a simple criterion for the strength of epistasis that is necessary to overcome the twofold disadvantage of sex.     

蛋白质相互作用数据库及其应用

对蛋白质相互作用及其网络的了解不仅有助于深入理解生命活动的本质和疾病发生的机制,而且可以为药物研发提供靶点.目前,通过高通量筛选、计算方法预测和文献挖掘等方法,获得了大批量的蛋白质相互作用数据,并由此构建了很多内容丰富并日益更新的蛋白质相互作用数据库.本文首先简要阐述了大规模蛋白质相互作用数据产生的3种方法,然后重点介绍了几个人类相关的蛋白质相互作用公共数据库,包括HPRD、BIND、 IntAct、MINT、 DIP 和MIPS,并概述了蛋白质相互作用数据库的整合情况以及这些数据库在蛋白质相互作用网络构建上的应用.     

P-LISA技术

原位邻近式连接分析(proximity ligation in situ assay,P-LISA)是一种用来研究蛋白质-蛋白质相互作用的新方法。该方法能够对原位、瞬时、微弱的蛋白质-蛋白质相互作用进行定量分析和亚细胞定位,在药物研发和临床诊断中将有着重要的应用价值。     

Interactions between germ cells and somatic cells in Drosophila melanogaster

Interactions between germ cells and somatic cells are important at several stages of Drosophila development. The types of interactions that will be discussed include: (1) molecules physically transferred from one cell to another; (2) long range interactions by hormones; and (3) local interactions between germ cells and somatic cells when they are in close proximity. These interactions have been mostly characterized during oogenesis.     

Do biotic interactions modulate ecosystem functioning along stress gradients? Insights from semi-arid plant and biological soil crust communities

Climate change will exacerbate the degree of abiotic stress experienced by semi-arid ecosystems. While abiotic stress profoundly affects biotic interactions, their potential role as modulators of ecosystem responses to climate change is largely unknown. Using plants and biological soil crusts, we tested the relative importance of facilitative–competitive interactions and other community attributes (cover, species richness and species evenness) as drivers of ecosystem functioning along stress gradients in semi-arid Mediterranean ecosystems. Biotic interactions shifted from facilitation to competition along stress gradients driven by water availability and temperature. These changes were, however, dependent on the spatial scale and the community considered. We found little evidence to suggest that biotic interactions are a major direct influence upon indicators of ecosystem functioning (soil respiration, organic carbon, water-holding capacity, compaction and the activity of enzymes related to the carbon, nitrogen and phosphorus cycles) along stress gradients. However, attributes such as cover and species richness showed a direct effect on ecosystem functioning. Our results do not agree with predictions emphasizing that the importance of plant–plant interactions will be increased under climate change in dry environments, and indicate that reductions in the cover of plant and biological soil crust communities will negatively impact ecosystems under future climatic conditions.     

Protein folding in high-dimensional spaces: hypergutters and the role of nonnative interactions

We explore the consequences of very high dimensionality in the dynamical landscape of protein folding. Consideration of both typical range of stabilizing interactions, and folding rates themselves, leads to a model of the energy hypersurface that is characterized by the structure of diffusive "hypergutters" as well as the familiar "funnels". Several general predictions result: 1), intermediate subspaces of configurations will always be visited; 2), specific but nonnative interactions may be important in stabilizing these low-dimensional diffusive searches on the folding pathway, as well as native interactions; 3), sequential barriers will commonly be found, even in "two-state" proteins; 4), very early times will show characteristic departures from single-exponential kinetics; and 5), contributions of nonnative interactions to Phi-values and "Chevron plots" are calculable, and may be significant. The example of a three-helix bundle is treated in more detail as an illustration. The model also shows that high-dimensional structures provide conceptual relations between different models of protein folding. It suggests that kinetic strategies for fast folding may be encoded rather generally in nonnative as well as in native interactions. The predictions are related to very recent findings in experiment and simulation.     

Systems genetics in “-omics” era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP–SNP genetic interactions, LD block–block interactions, miRNA–mRNA interactions, DNA–protein interactions, protein–protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate “-omics” datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.     

Applications of BRET to study dynamic G-protein coupled receptor interactions in living cells

Summary Protein-protein interactions are fundamental processes for many biological systems including those involving the superfamily of G-protein coupled receptors (GPCRs). When addressing key questions concerning the regulation of GPCR-protein complexes and their functional significance, the development and refinement of non-invasive techniques to study these interactions will be of great value. One such technique, bioluminescence resonance energy transfer (BRET), is a recently described biophysical method that represents a powerful tool with which to measure protein-protein interactions in live cells, in real time. This minireview highlights the impact that evolving techniques such as BRET have had on the study of dynamic protein interactions involving GPCRs. In particular, the application of BRET to the study of protein interactions involving the receptors for hypothalamic peptide hormones, thyrotropin-releasing hormone (TRH) and gonadotropin-releasing hormone (GnRH), will be discussed. Using these receptors, BRET has successfully been used to demonstrate formation of both agonist-dependent and independent GPCR-GPCR complexes (oligomerization) and the agonist-dependent interaction of GPCRs with their intracellular adaptor protein partners, the arrestins. In summary, BRET is a highly snnsitive method that will not only aid in advancing our understanding of GPCR signalling and trafficking bout coud also potentially lead to the development of novel therapeutics that target these GPCR-protein complexes.     

Protein co-evolution, co-adaptation and interactions

Co-evolution has an important function in the evolution of species and it is clearly manifested in certain scenarios such as host–parasite and predator–prey interactions, symbiosis and mutualism. The extrapolation of the concepts and methodologies developed for the study of species co-evolution at the molecular level has prompted the development of a variety of computational methods able to predict protein interactions through the characteristics of co-evolution. Particularly successful have been those methods that predict interactions at the genomic level based on the detection of pairs of protein families with similar evolutionary histories (similarity of phylogenetic trees: mirrortree). Future advances in this field will require a better understanding of the molecular basis of the co-evolution of protein families. Thus, it will be important to decipher the molecular mechanisms underlying the similarity observed in phylogenetic trees of interacting proteins, distinguishing direct specific molecular interactions from other general functional constraints. In particular, it will be important to separate the effects of physical interactions within protein complexes (‘co-adaptation') from other forces that, in a less specific way, can also create general patterns of co-evolution.