Systems biology of Haemonchus contortus – Advancing biotechnology for parasitic nematode control

Yuanting Zheng, Neil D. Young, Tao Wang, Bill C.H. Chang, Jiangning Song, Robin B. Gasser

Research output: Contribution to journalReview ArticleResearchpeer-review

2 Citations (Scopus)

Abstract

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus contortus – a blood-feeding nematode of ruminants – is a major pathogen and a model for molecular and applied parasitology research. This review synthesises some key advances in understanding the molecular biology, genetic diversity and host-parasite interactions of H. contortus, highlighting its value for comparative studies with the free-living nematode Caenorhabditis elegans. Key themes include recent developments in genomic, transcriptomic and proteomic technologies and resources, which are illuminating critical molecular pathways, including the ubiquitination pathway, protease/protease inhibitor systems and the secretome of H. contortus. Some of these insights are providing a foundation for identifying essential genes and exploring their potential as targets for novel anthelmintics or vaccines, particularly in the face of widespread anthelmintic resistance. Advanced bioinformatic tools, such as machine learning (ML) algorithms and artificial intelligence (AI)-driven protein structure prediction, are enhancing annotation capabilities, facilitating and accelerating analyses of gene functions, and biological pathways and processes. This review also discusses the integration of these tools with cutting-edge single-cell sequencing and spatial transcriptomics to dissect host-parasite interactions at the cellular level. The discussion emphasises the importance of curated databases, improved culture systems and functional genomics platforms to translate molecular discoveries into practical outcomes, such as novel interventions. New research findings and resources not only advance research on H. contortus and related nematodes but may also pave the way for innovative solutions to the global challenges with anthelmintic resistance.

Original languageEnglish
Article number108567
Number of pages24
JournalBiotechnology Advances
Volume81
DOIs
Publication statusPublished - 1 Jul 2025

Keywords

  • Anthelmintic resistance
  • Artificial intelligence (AI)
  • Bioinformatics
  • Functional genomics
  • Genetic diversity
  • Genomic technologies
  • Haemonchus contortus
  • Host-parasite interactions
  • Machine learning (ML)
  • Molecular parasitology
  • Novel interventions
  • Parasitic nematodes
  • Protease systems
  • Proteomics
  • Secretome
  • Single-cell sequencing
  • Transcriptomics
  • Ubiquitination pathway

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