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模型设计共培养物适应的遗传基础。

The genetic basis for adaptation of model-designed syntrophic co-cultures.

机构信息

Department of Bioengineering, University of California, San Diego, La Jolla, United States of America.

Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, United States of America.

出版信息

PLoS Comput Biol. 2019 Mar 1;15(3):e1006213. doi: 10.1371/journal.pcbi.1006213. eCollection 2019 Mar.

Abstract

Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains-with diverse metabolic deficiencies-were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities.

摘要

了解微生物群落的基本特征可能对人类健康和应用生物技术产生深远的影响。尽管如此,对于形成可行的合成群落的遗传基础和进化策略,我们仍然知之甚少。通过在共培养中配对营养缺陷型突变体,已经证明可以在代谢偶联的情况下建立可行的新生大肠杆菌群落。构建了一种新的算法 OptAux,用于设计 61 种独特的多敲除大肠杆菌营养缺陷型菌株,这些菌株需要大量摄取代谢物才能生长。这些预测的敲除包括一系列来自主要生物合成子系统抑制的新型非特异性营养缺陷型。将三种 OptAux 预测的非特异性营养缺陷型菌株(具有不同的代谢缺陷)与 L-组氨酸营养缺陷型菌株共培养,并通过适应性实验室进化 (ALE) 进行优化。时程测序揭示了每个菌株为实现更高的群落生长速率而采用的遗传变化,并深入了解了适应共生小生境的机制。代谢和基因表达的群落模型用于预测进化群落的相对群落组成和基本特征。这项工作为新生群落形成的遗传策略提供了新的见解,并提供了一种前沿的计算方法来阐明赋予创建合作群落能力的代谢变化。

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