Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion DOI Creative Commons
Xinrun Yang, Tianjie Yang,

Z Zhang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Abstract Understanding how microbiomes resist pathogen invasion remains a key challenge in natural ecosystems. Here, we combined genome-scale metabolic models with synthetic community experiments to unravel the mechanisms driving suppression. We developed curated for each strain, incorporating 48 common resource utilization profiles fully capture their capacities. Trophic interactions inferred from accurately predicted outcomes, achieving an F1 score of 96% across 620 tests involving diverse microbial communities and nutrient environments. Importantly, considering both substrate metabolite features provided more holistic understanding In particular, cross-feeding metabolites within native emerged as crucial yet often overlooked predictors resistance, disproportionally favoring species over invaders. This study lays foundation designing disease-resistant microbiomes, broad implications mitigating exposure

Language: Английский

Exploring a unified definition of ecological complexity towards restoration DOI
Haoran Wu, Jed Soleiman, Jamie Bolam

et al.

Total Environment Advances, Journal Year: 2025, Volume and Issue: unknown, P. 200125 - 200125

Published: April 1, 2025

Language: Английский

Citations

0
Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion DOI Creative Commons
Xinrun Yang, Tianjie Yang,

Z Zhang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Abstract Understanding how microbiomes resist pathogen invasion remains a key challenge in natural ecosystems. Here, we combined genome-scale metabolic models with synthetic community experiments to unravel the mechanisms driving suppression. We developed curated for each strain, incorporating 48 common resource utilization profiles fully capture their capacities. Trophic interactions inferred from accurately predicted outcomes, achieving an F1 score of 96% across 620 tests involving diverse microbial communities and nutrient environments. Importantly, considering both substrate metabolite features provided more holistic understanding In particular, cross-feeding metabolites within native emerged as crucial yet often overlooked predictors resistance, disproportionally favoring species over invaders. This study lays foundation designing disease-resistant microbiomes, broad implications mitigating exposure

Language: Английский

Citations

0