Dataset Information

Host-pathogen interaction profiling using self-assembling human protein arrays.

ABSTRACT: Host-pathogen protein interactions are fundamental to every microbial infection, yet their identification has remained challenging due to the lack of simple detection tools that avoid abundance biases while providing an open format for experimental modifications. Here, we applied the Nucleic Acid-Programmable Protein Array and a HaloTag-Halo ligand detection system to determine the interaction network of Legionella pneumophila effectors (SidM and LidA) with 10?000 unique human proteins. We identified known targets of these L. pneumophila proteins and potentially novel interaction candidates. In addition, we applied our Click chemistry-based NAPPA platform to identify the substrates for SidM, an effector with an adenylyl transferase domain that catalyzes AMPylation (adenylylation), the covalent addition of adenosine monophosphate (AMP). We confirmed a subset of the novel SidM and LidA targets in independent in vitro pull-down and in vivo cell-based assays, and provided further insight into how these effectors may discriminate between different host Rab GTPases. Our method circumvents the purification of thousands of human and pathogen proteins, and does not require antibodies against or prelabeling of query proteins. This system is amenable to high-throughput analysis of effectors from a wide variety of human pathogens that may bind to and/or post-translationally modify targets within the human proteome.

SUBMITTER: Yu X

PROVIDER: S-EPMC4467460 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Host-pathogen interaction profiling using self-assembling human protein arrays.

Yu Xiaobo X Decker Kimberly B KB Barker Kristi K Neunuebel M Ramona MR Saul Justin J Graves Morgan M Westcott Nathan N Hang Howard H LaBaer Joshua J Qiu Ji J Machner Matthias P MP

Journal of proteome research 20150318 4

Host-pathogen protein interactions are fundamental to every microbial infection, yet their identification has remained challenging due to the lack of simple detection tools that avoid abundance biases while providing an open format for experimental modifications. Here, we applied the Nucleic Acid-Programmable Protein Array and a HaloTag-Halo ligand detection system to determine the interaction network of Legionella pneumophila effectors (SidM and LidA) with 10 000 unique human proteins. We ident ...[more]

PMID: 25739981

Similar Datasets

Project description:BackgroundInfectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.ResultsAs host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins' marker.ConclusionsDifferent centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens' favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.

Dataset Information

Host-pathogen interaction profiling using self-assembling human protein arrays.

Publications

Host-pathogen interaction profiling using self-assembling human protein arrays.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets