Protein-protein interactions in pathogen recognition by plants

Protein-protein interactions have emerged as key determinants of whether plant encounters with pathogens result in disease or successful plant defense. Genetic interactions between plant resistance genes and pathogen avirulence genes enable pathogen recognition by plants and activate plant defense. These gene-for-gene interactions in some cases have been shown to involve direct interactions of the products of the genes, and have indicated plant intracellular localization for certain avirulence proteins. Incomplete specificity of some of the interactions in laboratory assays suggests that additional proteins might be required to confer specificity in the plant. In many cases, resistance and avirulence protein interactions have not been demonstrable, and in some cases, other plant components that interact with avirulence proteins have been found. Investigation to date has relied heavily on biochemical and cytological methods including in vitrobinding assays and immunoprecipitation, as well as genetic tools such as the yeast two-hybrid system. Observations so far, however, point to the likely requirement for multiple, interdependent protein associations in pathogen recognition, for which these techniques can be insufficient. This article reviews the protein-protein interactions that have been described in pathogen recognition by plants, and provides examples of how rapid future progress will hinge on the adoption of new and developing technologies.     

Recognition of nucleic acid bases and base-pairs by hydrogen bonding to amino acid side-chains

Sequence-specific protein-nucleic acid recognition is determined, in part, by hydrogen bonding interactions between amino acid side-chains and nucleotide bases. To examine the repertoire of possible interactions, we have calculated geometrically plausible arrangements in which amino acids hydrogen bond to unpaired bases, such as those found in RNA bulges and loops, or to the 53 possible RNA base-pairs. We find 32 possible interactions that involve two or more hydrogen bonds to the six unpaired bases (including protonated A and C), 17 of which have been observed. We find 186 "spanning" interactions to base-pairs in which the amino acid hydrogen bonds to both bases, in principle allowing particular base-pairs to be selectively targeted, and nine of these have been observed. Four calculated interactions span the Watson-Crick pairs and 15 span the G:U wobble pair, including two interesting arrangements with three hydrogen bonds to the Arg guanidinum group that have not yet been observed. The inherent donor-acceptor arrangements of the bases support many possible interactions to Asn (or Gln) and Ser (or Thr or Tyr), few interactions to Asp (or Glu) even though several already have been observed, and interactions to U (or T) only if the base is in an unpaired context, as also observed in several cases. This study highlights how complementary arrangements of donors and acceptors can contribute to base-specific recognition of RNA, predicts interactions not yet observed, and provides tools to analyze proposed contacts or design novel interactions.     

Combining different 'omics' technologies to map and validate protein-protein interactions in humans.

The mapping of protein-protein interactions is key to understanding biological processes. Many technologies have been reported to map interactions and these have been systematically applied in yeast. To date, the number of reported yeast protein interactions that have been truly validated by at least one other approach is low. The mapping of human protein interaction networks is even more complicated. Thus, it is unreasonable to try to map the human interactome; instead, interaction mapping in human cell lines should be focused along the lines of diseases or changes that can be associated with specific cells. In this paper, an approach for combining different 'omics' technologies to achieve efficient mapping and validation of protein interactions in human cell lines is presented.     

Function prediction and protein networks

In the genomics era, the interactions between proteins are at the center of attention. Genomic-context methods used to predict these interactions have been put on a quantitative basis, revealing that they are at least on an equal footing with genomics experimental data. A survey of experimentally confirmed predictions proves the applicability of these methods, and new concepts to predict protein interactions in eukaryotes have been described. Finally, the interaction networks that can be obtained by combining the predicted pair-wise interactions have enough internal structure to detect higher levels of organization, such as 'functional modules'.     

The function of peaceful post-conflict contacts among primates

Reconciliation has been the subject of considerable research in the last decade, and researchers have demonstrated that in many species of Old World monkeys and apes former opponents are more likely to engage in friendly interactions in the minutes that follow conflicts than they are at other times.de Waal has suggested that the function of these interactions is to mend relationships that have been damaged by conflict. Although peaceful post-conflict interactions are thought to have long-term effects upon the nature of social relationships, behavioral evidence presently indicates that the effects of these interactions may be limited to the post-conflict period. Theoretical considerations also raise some doubts about whether the relationship-repair hypothesis is cogent. Data that demonstrate that peaceful post-conflict interactions facilitate peaceful interactions and relieve victim's uncertainty and anxiety about whether conflict will be continued suggest that peaceful post-conflict interactions may be a means to reestablish contact with former opponents. Thus, they appear to function as predictive signals that the actor is going to stop fighting and behave peacefully. Such signals may be important in a broad range of social contexts.     

Pathfinding in a large vertebrate axon tract: isotypic interactions guide retinotectal axons at multiple choice points

Navigating axons respond to environmental guidance signals, but can also follow axons that have gone before - pioneer axons. Pioneers have been studied extensively in simple systems, but the role of axon-axon interactions remains largely unexplored in large vertebrate axon tracts, where cohorts of identical axons could potentially use isotypic interactions to guide each other through multiple choice points. Furthermore, the relative importance of axon-axon interactions compared with axon-autonomous receptor function has not been assessed. Here, we test the role of axon-axon interactions in retinotectal development, by devising a technique to selectively remove or replace early-born retinal ganglion cells (RGCs). We find that early RGCs are both necessary and sufficient for later axons to exit the eye. Furthermore, introducing misrouted axons by transplantation reveals that guidance from eye to tectum relies heavily on interactions between axons, including both pioneer-follower and community effects. We conclude that axon-axon interactions and ligand-receptor signaling have co-equal roles, cooperating to ensure the fidelity of axon guidance in developing vertebrate tracts.     

Ball and socket figures between secretory vesicles in mammary epithelial cells

Summary Interaction of adjacent secretory vesicles through ball and socket figures was observed in milk secreting mammary epithelial cells preserved by quick freezing without chemical fixation. Membranes of adjacent vesicles appeared to be fused together. Such vesicle-vesicle interactions have been described in chemically fixed tissues, but it has been argued that these interactions may have been fixation artifacts. Ball and socket figures in quick-frozen cells were smaller than those in chemically fixed cells. However, their existence in cells arrested by quick freezing argues that such vesicle-vesicle interactions occur in living cells.     

Computational structural analysis of protein interactions and networks

Protein interactions have been at the focus of computational biology in recent years. In particular, interest has come from two different communities--structural and systems biology. Here, we will discuss key systems and structural biology methods that have been used for analysis and prediction of protein-protein interactions and the insight these approaches have provided on the nature and organization of protein-protein interactions inside cells.     

Spinal, thalamic and cortical levels of splanchno-splanchnic interactions]

Using the occlusion method, we have shown splanchno splanchnic interactions on spinal, thalamic and cortical cells in cat. 1. At the first level, splanchno splanchnic interactions concern only the cells located in the Rexed V layer. The splanchnic fibres involved are small sized ones (Agammadelta, B and C types). 2. At the second level, splanchno splanchnic interactions have been observed in the VPL nucleus. The latencies of responses suggest that only large fibres are concerned. 3. At the third level, cortical cells of SI and SII areas have been studied. Splanchno splanchnic interactions have been elicited by different afferent splanchnic fibres (medullated and non medullated ones).     

NMR studies of protein interactions

Interactions of proteins with other macromolecules or small molecules play important roles in most biological processes. Often, such interactions are weak and transient, and the complexes do not easily crystallize. NMR spectroscopy has the unique ability to retrieve information about these interactions and is increasingly used. Recent methodological developments have helped characterize weak protein interactions, and have in particular been applied to the study of proteins that are mostly unfolded alone but form well-defined complexes upon interaction. In addition, NMR methods have been applied to the identification and characterization of small chemicals that inhibit protein function, a primary objective of rational drug design.     

Flower development

Several homeotic genes controlling flower development have been characterized in Antirrhinum and Arabidopsis. Comparisons of their mutant phenotypes, expression patterns and genetic interactions have revealed that many of the basic mechanisms controlling flower development have been conserved in evolution, although important differences in the balance and interactions of genes also exist.     

Looking towards label-free biomolecular interaction analysis in a high-throughput format: a review of new surface plasmon resonance technologies

Surface plasmon resonance (SPR) biosensors have enabled a wide range of applications in which researchers can monitor biomolecular interactions in real time. Owing to the fact that SPR can provide affinity and kinetic data, unique features in applications ranging from protein-peptide interaction analysis to cellular ligation experiments have been demonstrated. Although SPR has historically been limited by its throughput, new methods are emerging that allow for the simultaneous analysis of many thousands of interactions. When coupled with new protein array technologies, high-throughput SPR methods give users new and improved methods to analyze pathways, screen drug candidates and monitor protein-protein interactions.     

A Computationally Guided Protein-Interaction Screen Uncovers Coiled-Coil Interactions Involved in Vesicular Trafficking

Mapping protein-protein interactions at a domain or motif level can provide structural annotation of the interactome. The α-helical coiled coil is among the most common protein-interaction motifs, and proteins predicted to contain coiled coils participate in diverse biological processes. Here, we introduce a combined computational/experimental screening strategy that we used to uncover coiled-coil interactions among proteins involved in vesicular trafficking in Saccharomyces cerevisiae. A number of coiled-coil complexes have already been identified and reported to play important roles in this important biological process. We identify additional examples of coiled coils that can form physical associations. The computational strategy used to prioritize coiled-coil candidates for testing dramatically improved the efficiency of discovery in a large experimental screen. As assessed by comprehensive yeast two-hybrid assays, computational prefiltering retained 90% of positive interacting pairs and eliminated > 60% of negatives from a set of interaction candidates. The coiled-coil-mediated interaction network elucidated using the combined computational/experimental approach comprises 80 coiled-coil associations between 58 protein pairs, among which 21 protein interactions have not been previously reported in interaction databases and 26 interactions were previously known at the protein level but have now been localized to the coiled-coil motif. The coiled-coil-mediated interactions were specific rather than promiscuous, and many interactions could be recapitulated in a green fluorescent protein complementation assay. Our method provides an efficient route to discovering new coiled-coil interactions and uncovers a number of associations that may have functional significance for vesicular trafficking.     

A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1-human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1-human interaction network. Novel HIV-1-human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed.     

Non-trophic interactions in deserts: Facilitation,interference, and an endangered lizard species

Research on plant–animal interactions has been focused on direct consumer interactions (i.e. plants as resources), but non-trophic interactions including providing shelter or interference with movement can also affect the fine-scale distribution of animals. In particular, non-trophic interactions that are positive could support threatened animal populations. Positive interactions have been used in the restoration of plant communities, but have not yet been extended to the management of animal habitat. In this study, we tested the hypothesis that non-trophic interactions influence the occurrence of an endangered lizard species in an arid shrub-annual system. At a location known to have a population of blunt-nosed leopard lizards (Gambelia sila), we geotagged 700 shrubs, measured shrub morphometric traits, collected biomass samples, and surveyed for lizard presence using scat detection dogs over two years. Relative to 2014, in 2013 plant productivity was high and lizard scats were found more frequently in areas with low invasive grass cover (i.e. residual dry matter, RDM). In 2014, plant productivity was low because of an extreme drought year, and lizard scats were more frequently observed under shrub canopies, particularly those with relatively dense cover. These findings support the novel theory that positive non-trophic interactions are a critical form of plant–animal interactions in addition to consumption. Dominant shrubs can act as a foundation species by functioning as a basal node in structuring both plant and animal communities through a network of interactions. Managing dominant plants, in addition to habitat, is therefore important for conserving animal species in arid ecosystems.