Interaction variability shapes succession of synthetic microbial ecosystems.,Nature Communications

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Interaction variability shapes succession of synthetic microbial ecosystems.
Nature Communications ( IF 14.7 ) Pub Date : 2020-01-16 , DOI: 10.1038/s41467-019-13986-6
Feng Liu _{1,

2,

3,

4} , Junwen Mao _{1,

2,

5} , Wentao Kong _{1,

2} , Qiang Hua _{3,

4} , Youjun Feng ₆ , Rashid Bashir _{1,

7,

8} , Ting Lu _{1,

2,

9,

10,

11}

Affiliation

Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China.
School of Bioengineering, East China University of Science and Technology, Shanghai, China.
Department of Physics, Huzhou University, Huzhou, China.
School of Medicine, Zhejiang University, Hangzhou, China.
Micro and Nanotechnology Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Carle Illinois College of Medicine, Urbana, IL, USA.
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

Cellular interactions are a major driver for the assembly and functioning of microbial communities. Their strengths are shown to be highly variable in nature; however, it is unclear how such variations regulate community behaviors. Here we construct synthetic Lactococcus lactis consortia and mathematical models to elucidate the role of interaction variability in ecosystem succession and to further determine if casting variability into modeling empowers bottom-up predictions. For a consortium of bacteriocin-mediated cooperation and competition, we find increasing the variations of cooperation, from either altered labor partition or random sampling, drives the community into distinct structures. When the cooperation and competition are additionally modulated by pH, ecosystem succession becomes jointly controlled by the variations of both interactions and yields more diversified dynamics. Mathematical models incorporating variability successfully capture all of these experimental observations. Our study demonstrates interaction variability as a key regulator of community dynamics, providing insights into bottom-up predictions of microbial ecosystems.

中文翻译：

相互作用的变异性决定了合成微生物生态系统的演替。

细胞相互作用是微生物群落组装和功能的主要驱动力。事实证明，他们的长处差异很大。然而，尚不清楚这种变异如何调节社区行为。在这里，我们构建了乳酸乳球菌综合体和数学模型，以阐明相互作用变异性在生态系统演替中的作用，并进一步确定将变异性转化为模型是否可以实现自下而上的预测。对于由细菌素介导的合作与竞争的财团，我们发现合作的变化不断增加，无论是劳动分工的改变还是随机抽样的结果，都将社区带入了不同的结构。当合作与竞争受到pH值的额外调节时，生态系统演替通过相互作用的变化共同控制，并产生更多样化的动力学。包含可变性的数学模型成功地捕获了所有这些实验观察结果。我们的研究表明相互作用的可变性是社区动力学的关键调节因素，为深入了解微生物生态系统的自下而上的预测提供了见识。

更新日期：2020-01-17

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