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Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif

BACKGROUND: Effector secretion is a common strategy of pathogen in mediating host-pathogen interaction. Eight EPIYA-motif containing effectors have recently been discovered in six pathogens. Once these effectors enter host cells through type III/IV secretion systems (T3SS/T4SS), tyrosine in the EPIY...

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Autores principales: Xu, Shunfu, Zhang, Chao, Miao, Yi, Gao, Jianjiong, Xu, Dong
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999339/
https://www.ncbi.nlm.nih.gov/pubmed/21143776
http://dx.doi.org/10.1186/1471-2164-11-S3-S1
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author Xu, Shunfu
Zhang, Chao
Miao, Yi
Gao, Jianjiong
Xu, Dong
author_facet Xu, Shunfu
Zhang, Chao
Miao, Yi
Gao, Jianjiong
Xu, Dong
author_sort Xu, Shunfu
collection PubMed
description BACKGROUND: Effector secretion is a common strategy of pathogen in mediating host-pathogen interaction. Eight EPIYA-motif containing effectors have recently been discovered in six pathogens. Once these effectors enter host cells through type III/IV secretion systems (T3SS/T4SS), tyrosine in the EPIYA motif is phosphorylated, which triggers effectors binding other proteins to manipulate host-cell functions. The objectives of this study are to evaluate the distribution pattern of EPIYA motif in broad biological species, to predict potential effectors with EPIYA motif, and to suggest roles and biological functions of potential effectors in host-pathogen interactions. RESULTS: A hidden Markov model (HMM) of five amino acids was built for the EPIYA-motif based on the eight known effectors. Using this HMM to search the non-redundant protein database containing 9,216,047 sequences, we obtained 107,231 sequences with at least one EPIYA motif occurrence and 3115 sequences with multiple repeats of the EPIYA motif. Although the EPIYA motif exists among broad species, it is significantly over-represented in some particular groups of species. For those proteins containing at least four copies of EPIYA motif, most of them are from intracellular bacteria, extracellular bacteria with T3SS or T4SS or intracellular protozoan parasites. By combining the EPIYA motif and the adjacent SH2 binding motifs (KK, R4, Tarp and Tir), we built HMMs of nine amino acids and predicted many potential effectors in bacteria and protista by the HMMs. Some potential effectors for pathogens (such as Lawsonia intracellularis, Plasmodium falciparum and Leishmania major) are suggested. CONCLUSIONS: Our study indicates that the EPIYA motif may be a ubiquitous functional site for effectors that play an important pathogenicity role in mediating host-pathogen interactions. We suggest that some intracellular protozoan parasites could secrete EPIYA-motif containing effectors through secretion systems similar to the T3SS/T4SS in bacteria. Our predicted effectors provide useful hypotheses for further studies.
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spelling pubmed-29993392010-12-09 Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif Xu, Shunfu Zhang, Chao Miao, Yi Gao, Jianjiong Xu, Dong BMC Genomics Research BACKGROUND: Effector secretion is a common strategy of pathogen in mediating host-pathogen interaction. Eight EPIYA-motif containing effectors have recently been discovered in six pathogens. Once these effectors enter host cells through type III/IV secretion systems (T3SS/T4SS), tyrosine in the EPIYA motif is phosphorylated, which triggers effectors binding other proteins to manipulate host-cell functions. The objectives of this study are to evaluate the distribution pattern of EPIYA motif in broad biological species, to predict potential effectors with EPIYA motif, and to suggest roles and biological functions of potential effectors in host-pathogen interactions. RESULTS: A hidden Markov model (HMM) of five amino acids was built for the EPIYA-motif based on the eight known effectors. Using this HMM to search the non-redundant protein database containing 9,216,047 sequences, we obtained 107,231 sequences with at least one EPIYA motif occurrence and 3115 sequences with multiple repeats of the EPIYA motif. Although the EPIYA motif exists among broad species, it is significantly over-represented in some particular groups of species. For those proteins containing at least four copies of EPIYA motif, most of them are from intracellular bacteria, extracellular bacteria with T3SS or T4SS or intracellular protozoan parasites. By combining the EPIYA motif and the adjacent SH2 binding motifs (KK, R4, Tarp and Tir), we built HMMs of nine amino acids and predicted many potential effectors in bacteria and protista by the HMMs. Some potential effectors for pathogens (such as Lawsonia intracellularis, Plasmodium falciparum and Leishmania major) are suggested. CONCLUSIONS: Our study indicates that the EPIYA motif may be a ubiquitous functional site for effectors that play an important pathogenicity role in mediating host-pathogen interactions. We suggest that some intracellular protozoan parasites could secrete EPIYA-motif containing effectors through secretion systems similar to the T3SS/T4SS in bacteria. Our predicted effectors provide useful hypotheses for further studies. BioMed Central 2010-12-01 /pmc/articles/PMC2999339/ /pubmed/21143776 http://dx.doi.org/10.1186/1471-2164-11-S3-S1 Text en Copyright ©2010 Xu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Xu, Shunfu
Zhang, Chao
Miao, Yi
Gao, Jianjiong
Xu, Dong
Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title_full Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title_fullStr Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title_full_unstemmed Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title_short Effector prediction in host-pathogen interaction based on a Markov model of a ubiquitous EPIYA motif
title_sort effector prediction in host-pathogen interaction based on a markov model of a ubiquitous epiya motif
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999339/
https://www.ncbi.nlm.nih.gov/pubmed/21143776
http://dx.doi.org/10.1186/1471-2164-11-S3-S1
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