<p>The intestinal barrier is a dynamic interface integrating epithelial integrity, mucus architecture, and immune signaling to maintain host homeostasis. While microbial metabolites such as short-chain fatty acids, secondary bile acids, and tryptophan derivatives regulate this system, translating these insights to human physiology is hindered by experimental models that fail to capture the intestine’s full biological complexity. In this review, we conceptualize intestinal barrier failure as a sequential process comprising junctional remodeling, mucus depletion, and immune-driven permeability. We critically evaluate current in vitro and ex vivo models, highlighting how metabolic biases and reductionist designs in common platforms limit their predictive value. We argue that the primary bottleneck is not a lack of model diversity, but the absence of integrative, human-relevant strategies. Consequently, we propose a stepwise framework linking dynamic microbial fermentation to mechanistic epithelial systems and ex vivo human tissues. This approach moves beyond descriptive modeling toward functionally predictive platforms that align microbial metabolism with host responses across biological scales, ultimately informing clinical translation, precision nutrition, and therapeutic development.</p>

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Experimental models for intestinal host-microbe interactions

  • Yuqi Li,
  • Naschla Gasaly,
  • Paul de Vos

摘要

The intestinal barrier is a dynamic interface integrating epithelial integrity, mucus architecture, and immune signaling to maintain host homeostasis. While microbial metabolites such as short-chain fatty acids, secondary bile acids, and tryptophan derivatives regulate this system, translating these insights to human physiology is hindered by experimental models that fail to capture the intestine’s full biological complexity. In this review, we conceptualize intestinal barrier failure as a sequential process comprising junctional remodeling, mucus depletion, and immune-driven permeability. We critically evaluate current in vitro and ex vivo models, highlighting how metabolic biases and reductionist designs in common platforms limit their predictive value. We argue that the primary bottleneck is not a lack of model diversity, but the absence of integrative, human-relevant strategies. Consequently, we propose a stepwise framework linking dynamic microbial fermentation to mechanistic epithelial systems and ex vivo human tissues. This approach moves beyond descriptive modeling toward functionally predictive platforms that align microbial metabolism with host responses across biological scales, ultimately informing clinical translation, precision nutrition, and therapeutic development.