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Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica

Entamoeba histolytica is an invasive, pathogenic parasite causing amoebiasis. Given that proteins involved in transmembrane (TM) transport are crucial for the adherence, invasion, and nutrition of the parasite, we conducted a genome-wide bioinformatics analysis of encoding proteins to functionally c...

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Autores principales: Anwar, Tamanna, Samudrala, Gourinath
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209943/
https://www.ncbi.nlm.nih.gov/pubmed/30332795
http://dx.doi.org/10.3390/genes9100499
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author Anwar, Tamanna
Samudrala, Gourinath
author_facet Anwar, Tamanna
Samudrala, Gourinath
author_sort Anwar, Tamanna
collection PubMed
description Entamoeba histolytica is an invasive, pathogenic parasite causing amoebiasis. Given that proteins involved in transmembrane (TM) transport are crucial for the adherence, invasion, and nutrition of the parasite, we conducted a genome-wide bioinformatics analysis of encoding proteins to functionally classify and characterize all the TM proteins in E. histolytica. In the present study, 692 TM proteins have been identified, of which 546 are TM transporters. For the first time, we report a set of 141 uncharacterized proteins predicted as TM transporters. The percentage of TM proteins was found to be lower in comparison to the free-living eukaryotes, due to the extracellular nature and functional diversification of the TM proteins. The number of multi-pass proteins is larger than the single-pass proteins; though both have their own significance in parasitism, multi-pass proteins are more extensively required as these are involved in acquiring nutrition and for ion transport, while single-pass proteins are only required at the time of inciting infection. Overall, this intestinal parasite implements multiple mechanisms for establishing infection, obtaining nutrition, and adapting itself to the new host environment. A classification of the repertoire of TM transporters in the present study augments several hints on potential methods of targeting the parasite for therapeutic benefits.
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spelling pubmed-62099432018-11-02 Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica Anwar, Tamanna Samudrala, Gourinath Genes (Basel) Article Entamoeba histolytica is an invasive, pathogenic parasite causing amoebiasis. Given that proteins involved in transmembrane (TM) transport are crucial for the adherence, invasion, and nutrition of the parasite, we conducted a genome-wide bioinformatics analysis of encoding proteins to functionally classify and characterize all the TM proteins in E. histolytica. In the present study, 692 TM proteins have been identified, of which 546 are TM transporters. For the first time, we report a set of 141 uncharacterized proteins predicted as TM transporters. The percentage of TM proteins was found to be lower in comparison to the free-living eukaryotes, due to the extracellular nature and functional diversification of the TM proteins. The number of multi-pass proteins is larger than the single-pass proteins; though both have their own significance in parasitism, multi-pass proteins are more extensively required as these are involved in acquiring nutrition and for ion transport, while single-pass proteins are only required at the time of inciting infection. Overall, this intestinal parasite implements multiple mechanisms for establishing infection, obtaining nutrition, and adapting itself to the new host environment. A classification of the repertoire of TM transporters in the present study augments several hints on potential methods of targeting the parasite for therapeutic benefits. MDPI 2018-10-16 /pmc/articles/PMC6209943/ /pubmed/30332795 http://dx.doi.org/10.3390/genes9100499 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Anwar, Tamanna
Samudrala, Gourinath
Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title_full Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title_fullStr Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title_full_unstemmed Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title_short Bioinformatics Analysis and Functional Prediction of Transmembrane Proteins in Entamoeba histolytica
title_sort bioinformatics analysis and functional prediction of transmembrane proteins in entamoeba histolytica
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209943/
https://www.ncbi.nlm.nih.gov/pubmed/30332795
http://dx.doi.org/10.3390/genes9100499
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