Untargeted Metabolomics Sensitively Differentiates Gut Bacterial Species in Single Culture and Co-Culture Systems.
Untargeted Metabolomics Sensitively Differentiates Gut Bacterial Species in Single Culture and Co-Culture Systems.
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非靶向代谢组学灵敏地区分单一培养和共培养系统中的肠道细菌种类。
DOI：
10.1021/acsomega.1c07114
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发表时间：
2022-05-03
期刊：
影响因子：
4.1
通讯作者：
Zhu, Jiangjiang
中科院分区：
文献类型：
--
作者：
Zhang, Shiqi;Zhu, Jiangjiang
肠道微生物群对人类健康起着至关重要的作用，其特征已经通过下一代测序技术得到了广泛的鉴定。虽然对肠道微生物组有很好的基因组学见解，但它的功能信息并不是通过元基因组学技术清楚地阐述的。另一方面，粪便代谢组可以作为微生物组组成的功能读数；因此，我们设计了一项概念验证研究，首先描述不同肠道微生物的代谢组，然后研究共培养系统中细菌代谢物与其组成之间的关系。我们从双歧杆菌属(2)、类杆菌属(1)、乳杆菌属(4)和阿克曼属(1)中选取了8种具有代表性的细菌作为模式微生物。利用液-质联用非靶向代谢组学技术，对细菌单一培养和共培养体系的微生物代谢组进行了研究。通过光谱比较，我们的结果表明，非靶向代谢组学可以捕捉到8个有代表性的肠道细菌代谢谱的相似性和差异性。此外，根据我们的统计分析，非靶向代谢组学可以敏感地区分肠道细菌种类。例如，瓜氨酸和组胺水平在四种乳杆菌之间存在显著差异。此外，在不同细菌种群比例的共培养体系中，肠道细菌代谢产物可用于定量反映混合培养中的细菌种群。例如，2-羟基丁酸的相对丰度随共培养体系中罗氏乳杆菌种群比例的变化而成比例变化。综上所述，我们提出了一种工作流程，可以证明非靶向代谢组学在区分肠道细菌种类和检测其特征代谢物方面的能力，并按比例检测共培养系统中的微生物种群。
Gut microbiome plays a vital role in human health, and its characteristic has been widely identified through next-generation sequencing techniques. Although with great genomic insights into gut microbiome, its functional information is not clearly elaborated through metagenomic techniques. On the other hand, it is suggested that fecal metabolome can be used as a functional readout of the microbiome composition; therefore, we designed a proof-of-concept study to first characterize the metabolome of different gut microbes and then investigate the relationship between bacterial metabolomes and their compositions in co-culture systems. We selected eight representative bacteria species from Bifidobacterium (2), Bacteroides (1), Lactobacillus (4), and Akkermansia (1) genera as our model microbes. Liquid chromatography coupled mass spectrometry-based untargeted metabolomics was utilized to explore the microbial metabolome of bacteria single cultures and co-culture systems. Through spectral comparisons, our results showed that untargeted metabolomics could capture the similarity and differences in metabolic profiles from eight representative gut bacteria. Also, untargeted metabolomics could sensitively differentiate gut bacterial species based on our statistical analyses. For example, citrulline and histamine levels were significantly different among four Lactobacillus species. In addition, in the co-culture systems with different bacteria population ratios, gut bacterial metabolomes can be used to quantitatively reflect bacterial population in a mixed culture. For instance, the relative abundance of 2-hydroxybutyric acid changed proportionately with the changed population ratio of Lactobacillus reuteri in the co-culture system. In summary, we proposed a workflow that could demonstrate the capability of untargeted metabolomics in differentiating gut bacterial species and detecting their characteristic metabolites proportionally to the microbial population in co-culture systems.
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影响因子：
4.1
作者：
Mielko, Karolina Anna;Jablonski, Slawomir Jan;Mlynarz, Piotr
通讯作者：
Mlynarz, Piotr
影响因子：
3.2
作者：
TAYLOR, WH;TAYLOR, ML;EAMES, DF
通讯作者：
EAMES, DF
DOI：
10.1051/lait:2004036
发表时间：
2005-01-01
期刊：
LAIT
影响因子：
--
作者：
Thierry, A;Maillard, MB;Lortal, S
通讯作者：
Lortal, S
影响因子：
4
作者：
Barrett, E.;Ross, R. P.;Stanton, C.
通讯作者：
Stanton, C.
影响因子：
--
作者：
Saez-Lara MJ;Gomez-Llorente C;Plaza-Diaz J;Gil A
通讯作者：
Gil A