物种丰富度
成对比较
推论
生态学
分类等级
生物多样性
计算机科学
基因组
社区
微生物群
生物
人工智能
分类单元
生态系统
生物信息学
基因
生物化学
作者
Bryce Connors,Jaron C. Thompson,Ertmer Sarah,Ryan L. Clark,Brian F. Pfleger,Ophelia S. Venturelli
出处
期刊:Cell systems
[Elsevier BV]
日期:2023-12-01
卷期号:14 (12): 1044-1058.e13
被引量:17
标识
DOI:10.1016/j.cels.2023.11.007
摘要
Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper's transparent peer review process is included in the supplemental information.
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