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An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus

Major advances in genomic and associated technologies have demanded reliable bioinformatic tools and workflows for the annotation of genes and their products via comparative analyses using well-curated reference data sets, accessible in public repositories. However, the accurate in silico annotation...

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Autores principales: Zheng, Yuanting, Young, Neil D., Song, Jiangning, Chang, Bill C.H., Gasser, Robin B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10151223/
https://www.ncbi.nlm.nih.gov/pubmed/37143762
http://dx.doi.org/10.1016/j.csbj.2023.03.025
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author Zheng, Yuanting
Young, Neil D.
Song, Jiangning
Chang, Bill C.H.
Gasser, Robin B.
author_facet Zheng, Yuanting
Young, Neil D.
Song, Jiangning
Chang, Bill C.H.
Gasser, Robin B.
author_sort Zheng, Yuanting
collection PubMed
description Major advances in genomic and associated technologies have demanded reliable bioinformatic tools and workflows for the annotation of genes and their products via comparative analyses using well-curated reference data sets, accessible in public repositories. However, the accurate in silico annotation of molecules (proteins) encoded in organisms (e.g., multicellular parasites) which are evolutionarily distant from those for which these extensive reference data sets are available, including invertebrate model organisms (e.g., Caenorhabditis elegans – free-living nematode, and Drosophila melanogaster – the vinegar fly) and vertebrate species (e.g., Homo sapiens and Mus musculus), remains a major challenge. Here, we constructed an informatic workflow for the enhanced annotation of biologically-important, excretory/secretory (ES) proteins (“secretome”) encoded in the genome of a parasitic roundworm, called Haemonchus contortus (commonly known as the barber’s pole worm). We critically evaluated the performance of five distinct methods, refined some of them, and then combined the use of all five methods to comprehensively annotate ES proteins, according to gene ontology, biological pathways and/or metabolic (enzymatic) processes. Then, using optimised parameter settings, we applied this workflow to comprehensively annotate 2591 of all 3353 proteins (77.3%) in the secretome of H. contortus. This result is a substantial improvement (10–25%) over previous annotations using individual, “off-the-shelf” algorithms and default settings, indicating the ready applicability of the present, refined workflow to gene/protein sequence data sets from a wide range of organisms in the Tree-of-Life.
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spelling pubmed-101512232023-05-03 An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus Zheng, Yuanting Young, Neil D. Song, Jiangning Chang, Bill C.H. Gasser, Robin B. Comput Struct Biotechnol J Research Article Major advances in genomic and associated technologies have demanded reliable bioinformatic tools and workflows for the annotation of genes and their products via comparative analyses using well-curated reference data sets, accessible in public repositories. However, the accurate in silico annotation of molecules (proteins) encoded in organisms (e.g., multicellular parasites) which are evolutionarily distant from those for which these extensive reference data sets are available, including invertebrate model organisms (e.g., Caenorhabditis elegans – free-living nematode, and Drosophila melanogaster – the vinegar fly) and vertebrate species (e.g., Homo sapiens and Mus musculus), remains a major challenge. Here, we constructed an informatic workflow for the enhanced annotation of biologically-important, excretory/secretory (ES) proteins (“secretome”) encoded in the genome of a parasitic roundworm, called Haemonchus contortus (commonly known as the barber’s pole worm). We critically evaluated the performance of five distinct methods, refined some of them, and then combined the use of all five methods to comprehensively annotate ES proteins, according to gene ontology, biological pathways and/or metabolic (enzymatic) processes. Then, using optimised parameter settings, we applied this workflow to comprehensively annotate 2591 of all 3353 proteins (77.3%) in the secretome of H. contortus. This result is a substantial improvement (10–25%) over previous annotations using individual, “off-the-shelf” algorithms and default settings, indicating the ready applicability of the present, refined workflow to gene/protein sequence data sets from a wide range of organisms in the Tree-of-Life. Research Network of Computational and Structural Biotechnology 2023-03-18 /pmc/articles/PMC10151223/ /pubmed/37143762 http://dx.doi.org/10.1016/j.csbj.2023.03.025 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Zheng, Yuanting
Young, Neil D.
Song, Jiangning
Chang, Bill C.H.
Gasser, Robin B.
An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title_full An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title_fullStr An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title_full_unstemmed An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title_short An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
title_sort informatic workflow for the enhanced annotation of excretory/secretory proteins of haemonchus contortus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10151223/
https://www.ncbi.nlm.nih.gov/pubmed/37143762
http://dx.doi.org/10.1016/j.csbj.2023.03.025
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