Marinos Georgios, Hamerich Inga K, Debray Reena, Obeng Nancy, Petersen Carola, Taubenheim Jan, Zimmermann Johannes, Blackburn Dana, Samuel Buck S, Dierking Katja, Franke Andre, Laudes Matthias, Waschina Silvio, Schulenburg Hinrich, Kaleta Christoph
Research Group Medical Systems Biology, University Hospital Schleswig-Holstein Campus Kiel, Kiel University, Kiel, Schleswig-Holstein, Germany.
Research Group Evolutionary Ecology and Genetics, Zoological Institute, Kiel University, Kiel, Schleswig-Holstein, Germany.
bioRxiv. 2023 Feb 18:2023.02.17.528811. doi: 10.1101/2023.02.17.528811.
The microbiome is increasingly receiving attention as an important modulator of host health and disease. However, while numerous mechanisms through which the microbiome influences its host have been identified, there is still a lack of approaches that allow to specifically modulate the abundance of individual microbes or microbial functions of interest. Moreover, current approaches for microbiome manipulation such as fecal transfers often entail a non-specific transfer of entire microbial communities with potentially unwanted side effects. To overcome this limitation, we here propose the concept of precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In a first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we present a metabolic modeling network framework that allows us to define precision prebiotics for a two-member microbiome model community comprising the immune-protective MYb11 and the persistent colonizer MYb71. Thus, we predicted compounds that specifically boost the abundance of the host-beneficial MYb11, four of which were experimentally validated (L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid). L-serine was further assessed , leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that constraint-based metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.
微生物组作为宿主健康和疾病的重要调节因子，越来越受到关注。然而，尽管已经确定了微生物组影响其宿主的众多机制，但仍然缺乏能够特异性调节感兴趣的单个微生物丰度或微生物功能的方法。此外，目前用于微生物组操纵的方法，如粪便移植，往往会导致整个微生物群落的非特异性转移，可能产生不良副作用。为了克服这一限制，我们在此提出了精准益生元的概念，即特异性调节感兴趣的微生物组成员物种的丰度。第一步，我们表明，由于代谢生态位重叠，通常不可能通过仅被目标物种而非群落中其他物种摄取的化合物来定义精准益生元。随后，我们提出了一个代谢建模网络框架，该框架使我们能够为包含免疫保护性MYb11和持久性定殖菌MYb71的双成员微生物组模型群落定义精准益生元。因此，我们预测了能够特异性提高宿主有益菌MYb11丰度的化合物，其中四种在实验中得到了验证（L-丝氨酸、L-苏氨酸、D-甘露醇和γ-氨基丁酸）。对L-丝氨酸进行了进一步评估，结果表明在蠕虫宿主中MYb11的丰度也有所增加。总体而言，我们的研究结果表明，基于约束的代谢建模是设计精准益生元的有效工具，而精准益生元是未来微生物组靶向治疗的重要基石。
