TY - JOUR
T1 - An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus
AU - Zheng, Yuanting
AU - Young, Neil D.
AU - Song, Jiangning
AU - Chang, Bill C.H.
AU - Gasser, Robin B.
N1 - Funding Information:
YTZ was supported by a Melbourne Research Scholarship and a Rowden White Award. This research was funded by grants from the Australian Research Council (ARC; LP180101085 , LP180101334 and LP190101209 ). This work was undertaken using the LIEF HPC-GPGPU facility, hosted at The University of Melbourne, and established with the assistance of ARC grant LE170100200 .
Funding Information:
YTZ was supported by a Melbourne Research Scholarship and a Rowden White Award. This research was funded by grants from the Australian Research Council (ARC; LP180101085, LP180101334 and LP190101209). This work was undertaken using the LIEF HPC-GPGPU facility, hosted at The University of Melbourne, and established with the assistance of ARC grant LE170100200.
Publisher Copyright:
© 2023 The Authors
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Excretory/secretory proteins
KW - Genome
KW - Haemonchus contortus
KW - Informatics
KW - Machine learning
KW - Parasitic nematode
KW - Protein annotation
KW - Proteome
UR - http://www.scopus.com/inward/record.url?scp=85153253534&partnerID=8YFLogxK
U2 - 10.1016/j.csbj.2023.03.025
DO - 10.1016/j.csbj.2023.03.025
M3 - Article
C2 - 37143762
AN - SCOPUS:85153253534
SN - 2001-0370
VL - 21
SP - 2696
EP - 2704
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
ER -