Untargeted Metabolomics Sensitively Differentiates Gut Bacterial Species in Single Culture and Co-Culture Systems

Abstract

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.