Dataset Information

14-3-3 phosphoprotein interaction networks - does isoform diversity present functional interaction specification?

ABSTRACT: The 14-3-3 proteins have emerged as major phosphoprotein interaction proteins and thereby constitute a key node in the Arabidopsis Interactome Map, a node through which a large number of important signals pass. Throughout their history of discovery and description, the 14-3-3s have been described as protein families and there has been some evidence that the different 14-3-3 family members within any organism might carry isoform-specific functions. However, there has also been evidence for redundancy of 14-3-3 function, suggesting that the perceived 14-3-3 diversity may be the accumulation of neutral mutations over evolutionary time and as some 14-3-3 genes develop tissue or organ-specific expression. This situation has led to a currently unresolved question - does 14-3-3 isoform sequence diversity indicate functional diversity at the biochemical or cellular level? We discuss here some of the key observations on both sides of the resulting debate, and present a set of contrastable observations to address the theory functional diversity does exist among 14-3-3 isoforms. The resulting model suggests strongly that there are indeed functional specificities in the 14-3-3s of Arabidopsis. The model further suggests that 14-3-3 diversity and specificity should enter into the discussion of 14-3-3 roles in signal transduction and be directly approached in 14-3-3 experimentation. It is hoped that future studies involving 14-3-3s will continue to address specificity in experimental design and analysis.

SUBMITTER: Paul AL

PROVIDER: S-EPMC3422896 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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14-3-3 phosphoprotein interaction networks - does isoform diversity present functional interaction specification?

Paul Anna-Lisa AL Denison Fiona C FC Schultz Eric R ER Zupanska Agata K AK Ferl Robert J RJ

Frontiers in plant science 20120820

The 14-3-3 proteins have emerged as major phosphoprotein interaction proteins and thereby constitute a key node in the Arabidopsis Interactome Map, a node through which a large number of important signals pass. Throughout their history of discovery and description, the 14-3-3s have been described as protein families and there has been some evidence that the different 14-3-3 family members within any organism might carry isoform-specific functions. However, there has also been evidence for redund ...[more]

PMID: 22934100

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Project description:MotivationIdentifying functional modules in protein-protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of 'higher than expected connectivity', those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks.ResultsIn this article, we propose a novel optimization formulation LCP(2) (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP(2) by random walk. A spectral approximate algorithm SLCP(2) is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP(2) to a new algorithm (greedy algorithm for LCP(2)) GLCP(2) to identify overlapping functional modules. We compare SLCP(2) and GLCP(2) with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP(2) outperform all other compared algorithms.Availability and implementationAll data and code are available at http://www.cse.usf.edu/~xqian/fmi/slcp2hop/.

Project description:Most of earth's biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change.

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14-3-3 phosphoprotein interaction networks - does isoform diversity present functional interaction specification?

Publications

14-3-3 phosphoprotein interaction networks - does isoform diversity present functional interaction specification?

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