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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.
Afiliação
  • Zheng Y; Faculty of Science, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia.
  • Young ND; Faculty of Science, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia.
  • Song J; Faculty of IT, Department of Data Science and AI, Monash University, Victoria, Australia.
  • Chang BCH; Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Victoria, Australia.
  • Gasser RB; Monash Data Futures Institute, Monash University, Victoria, Australia.
Comput Struct Biotechnol J ; 21: 2696-2704, 2023.
Article em En | MEDLINE | ID: mdl-37143762
ABSTRACT
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália