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Huang et al. Microbiome Res Rep 2024;3:30 https://dx.doi.org/10.20517/mrr.2024.14 Page 5 of 13

Figure 1. GuMI can coculture F. prausnitzii A2-165 with colonic epithelium from multiple donors for up to 4 days. (A) The general
workflow of the GuMI experiment includes monolayer seeding, hardware preparation, GuMI assembly, bacterial injection, and sampling;
(B) TEER value of monolayers at 48 hours after bacterial injection under static condition (Static), GuMI-FP or GuMI-NB. The monolayers
were derived from an uninflamed/unaffected region in the transverse colon from donor H462, a 15-year-old male with CD. *P < 0.05,
***P < 0.001, one-way ANOVA was performed with Tukey’s multiple comparisons test; (C) Brightfield images of monolayers at the end
of the GuMI experiment in Static, GuMI-NB, and GuMI-FP; (D) Growth of F. prausnitzii after 48 h of coculture in GuMI. *P < 0.05 two-
tailed unpaired t-test; (E) Brightfield images of monolayers. Coculture of F. prausnitzii with two donors, HC2978 and HC465 (ulcerative
colitis patient), was maintained for four days. Dendritic cells and macrophages were included underneath the monolayers; (F) TEER
values of monolayers in GuMI. P = 0.55, two-tailed unpaired t-test; (G) Bacterial density in the apical compartment of GuMI after four
days of coculture compared to the inoculum (0d). Note that the same inoculum (0d) applies to HC2978 and HC465. *P < 0.05,
**P < 0.01, two-tailed unpaired t-test. TEER: Transepithelial electric resistance; GuMI-FP: GuMI with F. prausnitzii; GuMI-NB: GuMI
without bacteria.

significantly changed by exposure to F. prausnitzii. This discrepancy leads to the hypothesis that
F. prausnitzii alters other metabolites and influences the colonic epithelial transcriptome. To test this, we
performed targeted metabolomic analysis (see Methods) to analyze the media collected from the apical
compartment of the HC2978 monolayer under three conditions, i.e., Static culture, GuMI with no bacteria,
and GuMI with F. prausnitzii (GuMI-FP, originated from the original name F. prausnitzii). Out of 169
chemicals analyzed, 76 metabolites were above the detection limit in at least one-third of the samples
[Supplementary Tables 1 and 2]. Principal component analysis indicates a clear separation among the three
conditions [Figure 2A]. Principal components 1 and 2 account for over 70% of the variance. We noted a
variation within each group, as the replicates from the same experimental repeat tended to cluster
[Figure 2B]. Statistical analysis identified metabolites that contribute to separating the three groups in the
PCA plot. These chemicals clustered into several clusters attributed to Static, GuMI-NB, and GuMI-FP,