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

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.