{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T02:31:14Z","timestamp":1787452274371,"version":"build-2736575974"},"reference-count":44,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T00:00:00Z","timestamp":1719446400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Australian Research Council (ARC)","award":["LP220200614"],"award-info":[{"award-number":["LP220200614"]}]},{"name":"Australian Research Council (ARC)","award":["LP180101085"],"award-info":[{"award-number":["LP180101085"]}]},{"name":"Oz Omics","award":["LP220200614"],"award-info":[{"award-number":["LP220200614"]}]},{"name":"Oz Omics","award":["LP180101085"],"award-info":[{"award-number":["LP180101085"]}]},{"name":"Boehringer Ingelheim Vetmedica GmbH","award":["LP220200614"],"award-info":[{"award-number":["LP220200614"]}]},{"name":"Boehringer Ingelheim Vetmedica GmbH","award":["LP180101085"],"award-info":[{"award-number":["LP180101085"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Over the years, comprehensive explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive functional genomic\u2013phenomic, genomic, transcriptomic, and proteomic data sets have enabled the discovery and characterisation of genes that are crucial for life, called \u2018essential genes\u2019. Recently, we investigated the feasibility of inferring essential genes from such data sets using advanced bioinformatics and showed that a machine learning (ML)-based workflow could be used to extract or engineer features from DNA, RNA, protein, and\/or cellular data\/information to underpin the reliable prediction of essential genes both within and between C. elegans and D. melanogaster. As these are two distantly related species within the Ecdysozoa, we proposed that this ML approach would be particularly well suited for species that are within the same phylum or evolutionary clade. In the present study, we cross-predicted essential genes within the phylum Nematoda (evolutionary clade V)\u2014between C. elegans and the pathogenic parasitic nematode H. contortus\u2014and then ranked and prioritised H. contortus proteins encoded by these genes as intervention (e.g., drug) target candidates. Using strong, validated predictors, we inferred essential genes of H. contortus that are involved predominantly in crucial biological processes\/pathways including ribosome biogenesis, translation, RNA binding\/processing, and signalling and which are highly transcribed in the germline, somatic gonad precursors, sex myoblasts, vulva cell precursors, various nerve cells, glia, or hypodermis. The findings indicate that this in silico workflow provides a promising avenue to identify and prioritise panels\/groups of drug target candidates in parasitic nematodes for experimental validation in vitro and\/or in vivo.<\/jats:p>","DOI":"10.3390\/ijms25137015","type":"journal-article","created":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T05:11:39Z","timestamp":1719465099000},"page":"7015","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Inference of Essential Genes of the Parasite Haemonchus contortus via Machine Learning"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0446-848X","authenticated-orcid":false,"given":"T\u00falio L.","family":"Campos","sequence":"first","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"},{"name":"Bioinformatics Core Facility, Aggeu Magalh\u00e3es Institute (Fiocruz), Recife 50740-465, PE, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9957-4674","authenticated-orcid":false,"given":"Pasi K.","family":"Korhonen","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8756-229X","authenticated-orcid":false,"given":"Neil D.","family":"Young","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1359-8913","authenticated-orcid":false,"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8031-9086","authenticated-orcid":false,"given":"Jiangning","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Data Science and AI, Faculty of IT, Monash University, Melbourne, VIC 3800, Australia"},{"name":"Biomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia"},{"name":"Monash Data Futures Institute, Monash University, Clayton, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Marhoefer","sequence":"additional","affiliation":[{"name":"Boehringer Ingelheim Animal Health, Binger Strasse 173, 55216 Ingelheim am Rhein, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5313-4852","authenticated-orcid":false,"given":"Bill C. H.","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6048-2636","authenticated-orcid":false,"given":"Paul M.","family":"Selzer","sequence":"additional","affiliation":[{"name":"Boehringer Ingelheim Animal Health, Binger Strasse 173, 55216 Ingelheim am Rhein, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4423-1690","authenticated-orcid":false,"given":"Robin B.","family":"Gasser","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.pt.2014.04.009","article-title":"Chasing helminths and their economic impact on farmed ruminants","volume":"30","author":"Charlier","year":"2014","journal-title":"Trends Parasitol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.ijpara.2016.07.001","article-title":"Haemonchus contortus: The then and now, and where to from here?","volume":"46","author":"Emery","year":"2016","journal-title":"Int. J. Parasitol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.pt.2020.09.004","article-title":"Antiparasitics in animal health\u2014Quoad vadis?","volume":"37","author":"Selzer","year":"2020","journal-title":"Trends Parasitol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/bs.apar.2019.12.003","article-title":"A perspective on the discovery of selected compounds with anthelmintic activity against the barber\u2019s pole worm\u2014Where to from here?","volume":"108","author":"Jiao","year":"2020","journal-title":"Adv. Parasitol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1097\/00001432-200312000-00008","article-title":"Drug resistance in nematodes: A paper tiger or a real problem?","volume":"16","author":"Kaminsky","year":"2003","journal-title":"Curr. Opin. Infect. Dis."},{"key":"ref_6","first-page":"18","article-title":"Anthelmintics resistance; how to overcome it?","volume":"8","author":"Shalaby","year":"2013","journal-title":"Iran J. Parasitol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/bs.apar.2016.02.012","article-title":"Anthelmintic resistance in Haemonchus contortus: History, mechanisms and diagnosis","volume":"93","author":"Kotze","year":"2016","journal-title":"Adv. Parasitol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1645\/14-703.1","article-title":"Anthelmintic drug discovery: Into the future","volume":"101","author":"Geary","year":"2015","journal-title":"J. Parasitol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1002\/med.21668","article-title":"Drug discovery technologies: Caenorhabditis elegans as a model for anthelmintic therapeutics","volume":"40","author":"Reguera","year":"2020","journal-title":"Med. Res. Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1016\/j.csbj.2020.05.008","article-title":"Predicting gene essentiality in Caenorhabditis elegans by feature engineering and machine-learning","volume":"15","author":"Campos","year":"2020","journal-title":"Comput. Struct. Biotechnol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Campos, T.L., Korhonen, P.K., Hofmann, A., Gasser, R.B., and Young, N.D. (2020). Combined use of feature engineering and machine-learning to predict essential genes in Drosophila melanogaster. NAR Genom. Bioinform., 22.","DOI":"10.1093\/nargab\/lqaa051"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-1-4939-6371-3_1","article-title":"FlyBase Consortium. Using FlyBase, a database of Drosophila genes & genomes","volume":"Volume 1478","author":"Dahmann","year":"2016","journal-title":"Drosophila: Methods in Molecular Biology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.molbiopara.2016.11.005","article-title":"WormBase ParaSite\u2014A comprehensive resource for helminth genomics","volume":"215","author":"Howe","year":"2017","journal-title":"Mol. Biochem. Parasitol."},{"key":"ref_14","first-page":"D762","article-title":"WormBase: A modern Model Organism Information Resource","volume":"48","author":"Harris","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.ydbio.2022.02.013","article-title":"The great small organisms of developmental genetics: Caenorhabditis elegans and Drosophila melanogaster","volume":"485","author":"Kimble","year":"2022","journal-title":"Dev. Biol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Campos, T.L., Korhonen, P.K., and Young, N.D. (2022). Cross-predicting essential genes between two model eukaryotic species using machine learning. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22105056"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Campos, T.L., Korhonen, P.K., Hofmann, A., Gasser, R.B., and Young, N.D. (2021). Harnessing model organism genomics to underpin the machine-learning-based prediction of essential genes in eukaryotes\u2014Biotechnological implications. Biotechnol. Adv., 54.","DOI":"10.1016\/j.biotechadv.2021.107822"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1016\/bs.apar.2016.02.017","article-title":"Functional genomics tools for Haemonchus contortus and lessons from other helminths","volume":"93","author":"Britton","year":"2016","journal-title":"Adv. Parasitol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Castelletto, M.L., Gang, S.S., and Hallem, E.A. (2020). Recent advances in functional genomics for parasitic nematodes of mammals. J. Exp. Biol., 223.","DOI":"10.1242\/jeb.206482"},{"key":"ref_20","first-page":"16","article-title":"Understanding Haemonchus contortus better through genomics and transcriptomics","volume":"93","author":"Gasser","year":"2016","journal-title":"Adv. Parasitol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Doyle, S.R., Tracey, A., Laing, R., Holroyd, N., Bartley, D., Bazant, W., Beasley, H., Beech, R., Britton, C., and Brooks, K. (2020). Genomic and transcriptomic variation defines the chromosome-scale assembly of Haemonchus contortus, a model gastrointestinal worm. Commun. Biol., 9.","DOI":"10.1101\/2020.02.18.945246"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1016\/j.pt.2022.06.002","article-title":"Improving helminth genome resources in the post-genomic era","volume":"38","author":"Doyle","year":"2022","journal-title":"Trends Parasitol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Schwarz, E.M., Korhonen, P.K., Campbell, B.E., Young, N.D., Jex, A.R., Jabbar, A., Hall, R.S., Mondal, A., Howe, A.C., and Pell, J. (2013). The genome and developmental transcriptome of the strongylid nematode Haemonchus contortus. Genome Biol., 14.","DOI":"10.1186\/gb-2013-14-8-r89"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, T., and Gasser, R.B. (2021). Prospects of using high-throughput proteomics to underpin the discovery of animal host-nematode interactions. Pathogens, 10.","DOI":"10.3390\/pathogens10070825"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1126\/science.aam8940","article-title":"Comprehensive single-cell transcriptional profiling of a multicellular organism","volume":"357","author":"Cao","year":"2017","journal-title":"Science"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Aromolaran, O., Aromolaran, D., Isewon, I., and Oyelade, J. (2021). Machine learning approach to gene essentiality prediction: A review. Brief. Bioinform., 22.","DOI":"10.1093\/bib\/bbab128"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1016\/j.csbj.2020.02.022","article-title":"Essential gene prediction in Drosophila melanogaster using machine learning approaches based on sequence and functional features","volume":"10","author":"Aromolaran","year":"2020","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Beder, T., Aromolaran, O., D\u00f6nitz, J., Tapanelli, S., Adedeji, E.O., Adebiyi, E., Bucher, G., and Koenig, R. (2021). Identifying essential genes across eukaryotes by machine learning. NAR Genom. Bioinform., 3.","DOI":"10.1093\/nargab\/lqab110"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Marques de Castro, G., Hastenreiter, Z., Silva Monteiro, T.A., Martins da Silva, T.T., and Pereira Lobo, F. (2022). Cross-species prediction of essential genes in insects. Bioinformatics, 6.","DOI":"10.1093\/bioinformatics\/btac009"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1016\/j.molcel.2015.04.028","article-title":"Choosing the right tool for the job: RNAi, TALEN, CRISPR","volume":"58","author":"Boettcher","year":"2015","journal-title":"Mol. Cell"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1186\/s13071-022-05211-z","article-title":"Transgenesis in parasitic helminths: A brief history and prospects for the future","volume":"15","author":"Quinzo","year":"2022","journal-title":"Parasit. Vectors"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1465","DOI":"10.1534\/genetics.119.302628","article-title":"The enigmatic Canal-Associated Neurons regulate Caenorhabditis elegans larval development through a cAMP signalling pathway","volume":"213","author":"Chien","year":"2019","journal-title":"Genetics"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"iyac014","DOI":"10.1093\/genetics\/iyac014","article-title":"Nematode chromosomes","volume":"221","author":"Carlton","year":"2022","journal-title":"Genetics"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"6384","DOI":"10.1038\/sj.onc.1209883","article-title":"Ribosome biogenesis and cell growth: mTOR coordinates transcription by all three classes of nuclear RNA polymerases","volume":"25","author":"Mayer","year":"2006","journal-title":"Oncogene"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1016\/j.bbamcr.2009.10.009","article-title":"Driving ribosome assembly","volume":"1803","author":"Kressler","year":"2010","journal-title":"Biochim. Biophys. Acta"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1093\/jmcb\/mjv014","article-title":"Ribosomal proteins: Functions beyond the ribosome","volume":"7","author":"Zhou","year":"2015","journal-title":"J. Mol. Cell Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1007\/978-1-4939-7737-6_15","article-title":"Using WormBase ParaSite: An integrated platform for exploring helminth genomic data","volume":"1757","author":"Bolt","year":"2018","journal-title":"Methods Mol. Biol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1016\/j.csbj.2024.01.008","article-title":"Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates","volume":"23","author":"Korhonen","year":"2024","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3387","DOI":"10.1093\/bioinformatics\/btx431","article-title":"DeepLoc: Prediction of protein subcellular localization using deep learning","volume":"33","author":"Armenteros","year":"2017","journal-title":"Bioinformatics"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Hug, L.A., Baker, B.J., Anantharaman, K., Brown, C.T., Probst, A.J., Castelle, C.J., Butterfield, C.N., Hernsdorf, A.W., Amano, Y., and Ise, K. (2016). A new view of the tree of life. Nat. Microbiol., 1.","DOI":"10.1038\/nmicrobiol.2016.48"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"D884","DOI":"10.1093\/nar\/gkaa942","article-title":"Ensembl 2021","volume":"49","author":"Howe","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Emms, D.M., and Kelly, S. (2019). OrthoFinder: Phylogenetic ortholog inference for comparative genomics. Genome Biol., 20.","DOI":"10.1186\/s13059-019-1832-y"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"W191","DOI":"10.1093\/nar\/gkz369","article-title":"g:Profiler: A web server for functional enrichment analysis and conversions of gene lists (2019 update)","volume":"47","author":"Raudvere","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"D687","DOI":"10.1093\/nar\/gkab1028","article-title":"The reactome pathway knowledgebase 2022","volume":"50","author":"Gillespie","year":"2022","journal-title":"Nucleic Acids Res."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/25\/13\/7015\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:05:55Z","timestamp":1760108755000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/25\/13\/7015"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,27]]},"references-count":44,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["ijms25137015"],"URL":"https:\/\/doi.org\/10.3390\/ijms25137015","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,27]]}}}