Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.

<h4>Background</h4>Type III secretion systems (T3SSs) are central to the pathogenesis and specifically deliver their secreted substrates (type III secreted proteins, T3SPs) into host cells. Since T3SPs play a crucial role in pathogen-host interactions, identifying them is crucial to our...

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Autores principales:	Xiaojiao Yang, Yanzhi Guo, Jiesi Luo, Xuemei Pu, Menglong Li
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2cff0225d25d4ad791fa5c098b239671
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spelling	oai:doaj.org-article:2cff0225d25d4ad791fa5c098b2396712021-11-18T08:39:19ZEffective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.1932-620310.1371/journal.pone.0084439https://doaj.org/article/2cff0225d25d4ad791fa5c098b2396712013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24391954/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Type III secretion systems (T3SSs) are central to the pathogenesis and specifically deliver their secreted substrates (type III secreted proteins, T3SPs) into host cells. Since T3SPs play a crucial role in pathogen-host interactions, identifying them is crucial to our understanding of the pathogenic mechanisms of T3SSs. This study reports a novel and effective method for identifying the distinctive residues which are conserved different from other SPs for T3SPs prediction. Moreover, the importance of several sequence features was evaluated and further, a promising prediction model was constructed.<h4>Results</h4>Based on the conservation profiles constructed by a position-specific scoring matrix (PSSM), 52 distinctive residues were identified. To our knowledge, this is the first attempt to identify the distinct residues of T3SPs. Of the 52 distinct residues, the first 30 amino acid residues are all included, which is consistent with previous studies reporting that the secretion signal generally occurs within the first 30 residue positions. However, the remaining 22 positions span residues 30-100 were also proven by our method to contain important signal information for T3SP secretion because the translocation of many effectors also depends on the chaperone-binding residues that follow the secretion signal. For further feature optimisation and compression, permutation importance analysis was conducted to select 62 optimal sequence features. A prediction model across 16 species was developed using random forest to classify T3SPs and non-T3 SPs, with high receiver operating curve of 0.93 in the 10-fold cross validation and an accuracy of 94.29% for the test set. Moreover, when performing on a common independent dataset, the results demonstrate that our method outperforms all the others published to date. Finally, the novel, experimentally confirmed T3 effectors were used to further demonstrate the model's correct application. The model and all data used in this paper are freely available at http://cic.scu.edu.cn/bioinformatics/T3SPs.zip.Xiaojiao YangYanzhi GuoJiesi LuoXuemei PuMenglong LiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e84439 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaojiao Yang Yanzhi Guo Jiesi Luo Xuemei Pu Menglong Li Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
description	<h4>Background</h4>Type III secretion systems (T3SSs) are central to the pathogenesis and specifically deliver their secreted substrates (type III secreted proteins, T3SPs) into host cells. Since T3SPs play a crucial role in pathogen-host interactions, identifying them is crucial to our understanding of the pathogenic mechanisms of T3SSs. This study reports a novel and effective method for identifying the distinctive residues which are conserved different from other SPs for T3SPs prediction. Moreover, the importance of several sequence features was evaluated and further, a promising prediction model was constructed.<h4>Results</h4>Based on the conservation profiles constructed by a position-specific scoring matrix (PSSM), 52 distinctive residues were identified. To our knowledge, this is the first attempt to identify the distinct residues of T3SPs. Of the 52 distinct residues, the first 30 amino acid residues are all included, which is consistent with previous studies reporting that the secretion signal generally occurs within the first 30 residue positions. However, the remaining 22 positions span residues 30-100 were also proven by our method to contain important signal information for T3SP secretion because the translocation of many effectors also depends on the chaperone-binding residues that follow the secretion signal. For further feature optimisation and compression, permutation importance analysis was conducted to select 62 optimal sequence features. A prediction model across 16 species was developed using random forest to classify T3SPs and non-T3 SPs, with high receiver operating curve of 0.93 in the 10-fold cross validation and an accuracy of 94.29% for the test set. Moreover, when performing on a common independent dataset, the results demonstrate that our method outperforms all the others published to date. Finally, the novel, experimentally confirmed T3 effectors were used to further demonstrate the model's correct application. The model and all data used in this paper are freely available at http://cic.scu.edu.cn/bioinformatics/T3SPs.zip.
format	article
author	Xiaojiao Yang Yanzhi Guo Jiesi Luo Xuemei Pu Menglong Li
author_facet	Xiaojiao Yang Yanzhi Guo Jiesi Luo Xuemei Pu Menglong Li
author_sort	Xiaojiao Yang
title	Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
title_short	Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
title_full	Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
title_fullStr	Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
title_full_unstemmed	Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.
title_sort	effective identification of gram-negative bacterial type iii secreted effectors using position-specific residue conservation profiles.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/2cff0225d25d4ad791fa5c098b239671
work_keys_str_mv	AT xiaojiaoyang effectiveidentificationofgramnegativebacterialtypeiiisecretedeffectorsusingpositionspecificresidueconservationprofiles AT yanzhiguo effectiveidentificationofgramnegativebacterialtypeiiisecretedeffectorsusingpositionspecificresidueconservationprofiles AT jiesiluo effectiveidentificationofgramnegativebacterialtypeiiisecretedeffectorsusingpositionspecificresidueconservationprofiles AT xuemeipu effectiveidentificationofgramnegativebacterialtypeiiisecretedeffectorsusingpositionspecificresidueconservationprofiles AT menglongli effectiveidentificationofgramnegativebacterialtypeiiisecretedeffectorsusingpositionspecificresidueconservationprofiles
_version_	1718421490587664384

Effective identification of Gram-negative bacterial type III secreted effectors using position-specific residue conservation profiles.

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