Control points for design of taxonomic composition in synthetic human gut communities

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Bryce M. Connors, Jaron Thompson, Sarah Ertmer, Ryan L. Clark, Brian F. Pfleger, Ophelia S. Venturelli
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引用次数: 0

Abstract

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.

Abstract Image

设计合成人类肠道群落分类组成的控制点
微生物群落为众多领域提供了巨大的潜力,但要对其进行系统控制仍具有挑战性。我们开发了一种两阶段方法,通过精确控制培养基成分和初始物种丰度来指导合成微生物群落的分类组成。通过结合高通量实验和计算建模,我们展示了预测和设计 10 人合成人类肠道群落多样性的能力。我们发现,可以利用支配单培养生长的关键环境因素来引导微生物群落达到所需的状态。此外,系统性的初始丰度变化也会导致群落组合的变化,并能通过动态生态模型推断出成对物种间的相互作用。这些相互作用与条件介质实验总体上是一致的,表明对高丰度群落的特定扰动可以为建立动态生态模型提供丰富的信息。该模型随后被用于设计低富集度群落,这些群落在较长时间内显示出较低或较高的时间分类变异性。补充信息中包含了本文透明的同行评审过程记录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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