2026-04-20 カリフォルニア大学サンディエゴ校（UCSD）
＜関連情報＞
- https://today.ucsd.edu/story/to-thwart-pathogens-researchers-are-giving-beneficial-microbes-what-they-really-want
- https://www.cell.com/cell/abstract/S0092-8674(26)00337-5
標的微生物叢改変のための競合と基質嗜好の予測 Predicting competition and substrate preferences for targeted microbiome alteration
Oriane Moyne ∙ Grant J. Norton ∙ Mahmoud Al-Bassam ∙ … ∙ Manuela Raffatellu ∙ Livia S. Zaramela ∙ Karsten Zengler
Cell Published:April 17, 2026
DOI:https://doi.org/10.1016/j.cell.2026.03.036
Graphical abstract
Highlights
- Translation measurements reveal how microbes allocate resources in communities
- Functional profiles predict microbial competition and niche allocation
- Predictions enable rational design of prebiotic and probiotic interventions
- Interventions enable targeted modulation of complex microbiomes in vitro and in vivo
Summary
Microbiome science has greatly expanded our understanding of microbial life and its roles in the environment and human health. Yet microbiome science often relies on descriptive, correlation-based approaches that limit causal insight and intentional intervention designs. Moving toward predictive and mechanistic understanding requires functional characterization of microbial interactions and metabolic preferences. Here, we present microbial interaction and niche determination (MIND), which quantifies mRNA translation prioritization to infer substrate preferences and competitive interactions in complex communities. Applied to synthetic communities, soil, human fecal samples, and a mouse model, MIND predicted microbial competition and substrate preferences, guiding precision prebiotic and probiotic interventions to selectively modulate community composition. Currently focused on competition and substrate utilization, MIND could be further extended to capture additional interactions and ecological niches. By linking functional measurements to ecological outcomes, MIND offers a broadly applicable framework for targeted microbiome manipulation and rational intervention design rooted in functional insight.
