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      Signatures of Pleiotropy, Economy and Convergent Evolution in a Domain-Resolved Map of Human–Virus Protein–Protein Interaction Networks

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      1 , 2 , 3 , *
      PLoS Pathogens
      Public Library of Science

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          Abstract

          A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are otherwise hidden in the traditional binary network, highlighting the power and necessity of high-resolution approaches in host-pathogen systems biology.

          Author Summary

          The goal of host-pathogen systems biology is to examine the complex interactions between species, such as those between a virus and its host. Analysis of protein-protein interaction (PPI) networks can identify general principles that distinguish between within-species and between-species interactions. However, PPI data are limited by their low resolution, and cannot provide detailed information about the physical mechanisms underlying interactions between proteins. Using protein domain-based annotation methods, we have constructed an integrated human-virus PPI network which better highlights the mechanistic differences between human-human and human-virus PPIs. Our findings suggest that viral proteins use unique strategies to interact with human proteins, a finding with significant implications for pathogen research.

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          Most cited references35

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          The Universal Protein Resource (UniProt) in 2010

          The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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            The IntAct molecular interaction database in 2010

            IntAct is an open-source, open data molecular interaction database and toolkit. Data is abstracted from the literature or from direct data depositions by expert curators following a deep annotation model providing a high level of detail. As of September 2009, IntAct contains over 200.000 curated binary interaction evidences. In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows ‘zooming in’ on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.
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              Anti-immunology: evasion of the host immune system by bacterial and viral pathogens.

              Multicellular organisms possess very sophisticated defense mechanisms that are designed to effectively counter the continual microbial insult of the environment within the vertebrate host. However, successful microbial pathogens have in turn evolved complex and efficient methods to overcome innate and adaptive immune mechanisms, which can result in disease or chronic infections. Although the various virulence strategies used by viral and bacterial pathogens are numerous, there are several general mechanisms that are used to subvert and exploit immune systems that are shared between these diverse microbial pathogens. The success of each pathogen is directly dependant on its ability to mount an effective anti-immune response within the infected host, which can ultimately result in acute disease, chronic infection, or pathogen clearance. In this review, we highlight and compare some of the many molecular mechanisms that bacterial and viral pathogens use to evade host immune defenses.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                December 2013
                December 2013
                5 December 2013
                : 9
                : 12
                : e1003778
                Affiliations
                [1 ]Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
                [2 ]Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [3 ]Department of Bioengineering, Faculty of Engineering, McGill University, Montreal, Quebec, Canada
                University of Texas at Austin, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: YX EAF SG. Performed the experiments: YX EAF SG. Analyzed the data: YX EAF SG. Contributed reagents/materials/analysis tools: YX EAF SG. Wrote the paper: YX EAF SG.

                Article
                PPATHOGENS-D-13-01421
                10.1371/journal.ppat.1003778
                3855575
                24339775
                cf44368b-841a-4138-bc83-89651d14d253
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 June 2013
                : 6 October 2013
                Page count
                Pages: 9
                Funding
                This work was supported by NSF CCF-1219007 (to YX). SG was supported by an NSF IGERT Fellowship (DGE-0654108), and an NSF GRFP Fellowship (DGE-0741448). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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