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甲烷营养菌与异养菌之间相互作用的探索与预测。

Exploration and prediction of interactions between methanotrophs and heterotrophs.

机构信息

KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure links 653, 9000 Gent, Belgium.

出版信息

Res Microbiol. 2013 Dec;164(10):1045-54. doi: 10.1016/j.resmic.2013.08.006. Epub 2013 Sep 4.

DOI:10.1016/j.resmic.2013.08.006
PMID:24012541
Abstract

Methanotrophs can form the basis of a methane-driven food web on which heterotrophic microorganisms can feed. In return, these heterotrophs can stimulate growth of methanotrophs in co-culture by providing growth additives. However, only a few specific interactions are currently known. We incubated nine methanotrophs with 25 heterotrophic strains in a pairwise miniaturized co-cultivation setup. Through principal component analysis and k-means clustering, methanotrophs and heterotrophs could be grouped according to their interaction behaviour, suggesting strain-dependent methanotroph-heterotroph complementarity. Co-cultivation significantly enhanced the growth parameters of three methanotrophs. This was most pronounced for Methylomonas sp. M5, with a threefold increase in maximum density and a fourfold increase in maximum increase in density in co-culture with Cupriavidus taiwanensis LMG 19424. In contrast, co-cultivation with Methylobacterium radiotolerans LMG 2269 and Pseudomonas aeruginosa LMG 12228 inhibited growth of most methanotrophs. Functional genomic analysis suggested the importance of vitamin metabolism for co-cultivation success. The generated data set was then successfully exploited as a proof-of-principle for predictive modelling of co-culture responses based on other interactions of the same heterotrophs and methanotrophs, yielding values of the area under the receiver operating characteristic curve of 0.73 upon 50% missing values for the maximum increase in density parameter. As such, these modelling-based tools were shown to hold great promise in reducing the amount of data that needs to be generated when conducting large co-cultivation studies.

摘要

产甲烷菌可以成为以甲烷为基础的食物网的基础,异养微生物可以以此为食。作为回报,这些异养菌可以通过提供生长添加剂来刺激共培养中的产甲烷菌生长。然而,目前只知道少数几种特定的相互作用。我们在一个小型化的共培养设置中,将 9 种产甲烷菌与 25 种异养菌进行共培养。通过主成分分析和 K-均值聚类,可以根据相互作用行为对产甲烷菌和异养菌进行分组,这表明菌株依赖的产甲烷菌-异养菌互补性。共培养显著提高了 3 种产甲烷菌的生长参数。对于与 Cupriavidus taiwanensis LMG 19424 共培养的 Methylomonas sp. M5 来说,这种效果最为显著,最大密度增加了三倍,最大密度增加了四倍。相比之下,与 Methylobacterium radiotolerans LMG 2269 和 Pseudomonas aeruginosa LMG 12228 共培养抑制了大多数产甲烷菌的生长。功能基因组分析表明,维生素代谢对于共培养的成功至关重要。然后,成功地利用生成的数据集作为基于同一异养菌和产甲烷菌的其他相互作用进行共培养响应预测建模的原理证明,在最大密度参数缺失 50%的情况下,获得的接收者操作特征曲线下面积值为 0.73。因此,这些基于模型的工具在减少进行大型共培养研究所需的数据量方面显示出巨大的潜力。

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