Metabolic interaction models recapitulate leaf microbiota ecology

• 成果类型: Article
• 署名作者: Schafer, Martin; Pacheco, Alan R.; Kunzler, Rahel; Bortfeld-Miller, Miriam; Field, Christopher M.; Vayena, Evangelia; Hatzimanikatis, Vassily; Vorholt, Julia A.
• 署名单位: Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-11067
• DOI: 10.1126/science.adf5121
• 发表日期: 2023-07-07
• 页码: 42-+
• 关键词: arabidopsis-thaliana; overlap; strains; degradation; communities; phenotype; QUALITY

摘要

Resource allocation affects the structure of microbiomes, including those associated with living hosts. Understanding the degree to which this dependency determines interspecies interactions may advance efforts to control host-microbiome relationships. We combined synthetic community experiments with computational models to predict interaction outcomes between plant-associated bacteria. We mapped the metabolic capabilities of 224 leaf isolates from Arabidopsis thaliana by assessing the growth of each strain on 45 environmentally relevant carbon sources in vitro. We used these data to build curated genome-scale metabolic models for all strains, which we combined to simulate >17,500 interactions. The models recapitulated outcomes observed in planta with >89% accuracy, highlighting the role of carbon utilization and the contributions of niche partitioning and cross-feeding in the assembly of leaf microbiomes.