High throughput approaches to understanding the interactions between host and gastrointestinal parasites

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About this Research Topic

Submission deadlines

  1. Manuscript Summary Submission Deadline 20 August 2025 | Manuscript Submission Deadline 17 December 2025

  2. This Research Topic is still accepting articles.

Background

Gastrointestinal (GI) parasites, including helminths and protozoa, are a major challenge to human and animal health, cause economic losses in agriculture and pose a global public health risk. Understanding host-parasite interactions is crucial for the development of targeted diagnostics, therapies and interventions. Traditional studies, while informative, often overlook the dynamic, multi-layered nature of these relationships. Advances in high-throughput technologies — such as next-generation sequencing, proteomics, metabolomics and CRISPR-based screening — have transformed parasitology. These tools enable large-scale analysis of genetic, transcriptomic, proteomic and metabolomic changes in both hosts and parasites. In addition, organoid models and in vitro systems provide controlled environments for the study of GI-parasite-host interactions and improve reproducibility and scalability. Computational biology and machine learning further enrich these approaches by revealing patterns and predicting complex outcomes. This field of research promises to uncover new mechanisms of host resistance and parasite survival and drive innovation in vaccines, antiparasitic drugs and treatments to improve global health.

The goal of this Research Topic is to use high-throughput techniques to gain a comprehensive understanding of interactions between hosts and gastrointestinal (GI) parasites. Using advanced technologies such as next-generation sequencing, proteomics, metabolomics and CRISPR-based screens, these studies will help identify genetic, transcriptomic and proteomic changes in hosts and parasites during infection. The integration of organoid models, in vitro systems and computational tools such as machine learning will enable the discovery of novel mechanisms underlying host resistance and parasite survival strategies. Ultimately, this research aims to translate these findings into practical applications, including the development of effective vaccines, antiparasitic therapies, diagnostic tools and targeted intervention strategies that contribute to improving human and animal health worldwide.

To gather further insights in this complex and evolving field, we welcome articles addressing, but not limited to, the following themes:

o Use of next-generation sequencing (NGS) to analyze host-parasite genetic interactions

o Application of proteomics and metabolomics in understanding GI parasite pathways

o Advances in CRISPR-based functional genomics to study host-parasite dynamics

o Development and utilization of organoid models and in vitro systems for GI studies

o Computational biology tools such as machine learning to improve data analysis and predictive modelling

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Keywords: high-throughput technologies, gastrointestinal parasites, host-parasite interactions, omics, CRISPR-based functional genomics, organoid models, in vitro systems, host immune response, diagnostic tools, antiparasitic therapies, systems biology, helminths

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