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The global crisis of multidrug-resistant bacteria and parasitic nematodes demands new approaches to infectious disease control. Emerging evidence suggests gastrointestinal nematodes and the host gut microbiota are inextricably linked in a complex "holobiont". Parasitic nematodes have evolved in microbe-rich environments for millennia, developing innate immune defenses. This evolutionary "arms race" has produced a diverse repertoire of antimicrobial peptides (AMPs) that can target bacteria and other gut microbiota. With over 5,000 AMP and AMP-like domain-encoding genes identified via computational mining, the bottleneck is validation. The integration of machine learning algorithms with advanced in vitro and ex vivo models will allow prediction of AMP mode of action, spectrum of activity and efficacy, followed by testing in organoids to address some of the limitations of animal models.
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Sutcliffe et al. (2026) studied this question.
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