Fig 2: Dietary n-3 PUFA supplementation reduces CPT-11-induced alterations in the gut microbiome. (A) Principal coordinates analysis (PCOA) plot showing the results of Bray–Curtis distance-based analysis of beta diversity metrics. (B) Violin plot with lines at the median (dashed lines) and quartiles (complete lines) showing the differences in the Pielou’s evenness index (α-diversity). (C) Microbe–microbe interactions network [SparCC correlation analysis (CO+CPT-11 vs. FO+CPT-11)]. Each node (*, GUSB-producing taxa; #, healthy gut making taxa) represents a taxon (colored based on the phylum level and sized based on the number of connections to that taxon). Two taxa are connected by an edge (co-occurrences: red; anti-occurrences: blue; p-value < 0.05 and correlation threshold 0.3; size reflects the magnitude). (D) Random Forests classification of taxa (genus level) of CPT-11 treated CO and FO groups. (E) Composition summary showing the phyla detected in the CPT-11 treated CO and FO groups. The numbers above each bar show the relative abundance (RA) of the Proteobacteria phylum. (F–I) RA of differentially abundant bacterial groups such as Enterobacteriaceae (F) with representative colonic luminal contents MacConkey agar culture plate photos (G) showing the difference (H) in the growth of Escherichia Coli and Bifidobacterium (I), which is not detectable in CO group. (J) qPCR results showing the RA of beta-glucuronidase (GUSB)-producing bacteria. (K) The difference in GUSB activity was measured at baseline (BL) and days (d) 6 using stool samples and at days 11 using cecal contents. (L) Representative pictures are showing GUSB expression measured at proximal colon using the immunohistochemical technique. (M) RA of GUSB (K01195) gene predicted using PICRUSt2. Data are shown as mean ± standard error of the mean. Data with different superscript letters are significantly different (p < 0.05) according to the nonparametric Mann–Whitney test (* p < 0.05, ** p < 0.01) or ordinary two-way (K) ANOVA followed by Sidak’s multiple comparisons tests. Scale bar for images in (J) panel: 2000 μm.

Fig 3: Decreased tissue n-6/n-3 ratio prevents CPT-11-induced alterations in the gut microbiome. (A) Principal coordinates analysis (PCOA) plot showing the results of Bray–Curtis distance-based analysis of beta diversity metrics. (B) Violin plot with lines at the median (dashed lines) and quartiles (complete lines) showing the differences in the Pielou’s evenness index. (C) Microbe–microbe interactions network [SparCC correlation analysis (WT+CPT-11 vs. FAT-1+CPT-11)]. Each node (*, GUSB-producing taxa; #, healthy gut making taxa) represents a taxon (colored based on the phylum level and sized based on the number of connections to that taxon). Two taxa are connected by an edge (co-occurrences: red; anti-occurrences: blue; p-value < 0.05 and correlation threshold 0.3; size reflects the magnitude). (D) Random Forests classification of taxa (genus level) in the vehicle (W and F1) or CPT-11 (WC and F1C) treated groups. (E) Phyla detected in the control and CPT-11 treated WT and FAT-1 mice. The numbers above each group show the relative abundance (RA) of the Proteobacteria phylum. (F–K) RA of differentially abundant (ANCOM test by QIIME2) bacterial groups such as Enterobacteriaceae (F) with representative colonic luminal contents MacConkey agar culture plate photos (G) showing the difference (H) in the growth of Escherichia Coli (pink colonies), Enterococcus (I), Bifidobacterium (J) and Akkermansia (K). (L) RA of beta-glucuronidase (GUSB)-producing bacteria measured using qPCR. (M) The difference in GUSB activity was measured at baseline (BL) and days (d) 6 using stool samples and at days 11 using cecal contents. (N) Immunohistochemical staining-based GUSB gene expression patterns in the proximal colon. (O) RA of GUSB (K01195) gene predicted using PICRUSt2. Data are shown as mean ± standard error of the mean. Data with different superscript letters are significantly different (p < 0.05) according to the Kruskal–Wallis test (B) or Mann–Whitney test, or ordinary two-way (M) ANOVA followed by Sidak’s multiple comparisons test. Scale bar for images in (J) panel: 2000 μm.

Fig 4: MPA reactivation rates correlate with β-GUSgene variants linked with Faecalibacterium prausnitzii. Correlations between MPA reactivation rates and read mapping rates to beta-glucuronidase (β-GUS) gene variants filtered to represent only those variants observed in at least 50% of kidney transplant recipients (a) and healthy individuals (b), as well as mean normalized abundances of those genes with error bars representing ± 1 s.e. (c, d). Green and beige bars represent β-GUS genes linked with Faecalibacterium prausnitzii in a/c and b/d, respectively. See Supplementary Fig. S7 for a more detailed label with the specific gene markers and Supplementary Fig. S8a and b for correlations between MPA reactivation rates and all observed β-GUS gene variants. *p < 0.05; **p < 0.01; ***p < 0.001. RPKM, reads per kilobase of target sequence per million reads in library

Fig 5: Decreased tissue n-6/n-3 ratio reduces CPT-11-induced imbalances in the host–gut microbiome interactions. (A,B) Host–microbiota interaction network built from Spearman’s nonparametric rank correlation coefficient (p < 0.05) between host parameters and entire microbial parameters (genus-level) of WT+CPT-11 vs. FAT-1+CPT-1 (A) and CO+CPT-11 vs. FO+CPT-11 (B) comparisons. Nodes (filled squares) in panel A represent host parameters (cyan) and microbes (olive). Nodes in panel B represent host parameters (filled squares colored black) and microbes (different shapes indicate different phylum and colored light black). Lines (edges) represent statistically significant correlations (p < 0.05) and are colored blue for positive and red for negative correlations. Edge size reflects the magnitude of the correlation. (C) Multiple Factor Analysis superimposing the host and gut microbiome (genus-level) data associated with a high tissue n-6/n-3 ratio (WT+CPT-11/CO+CPT-11 samples) and a low tissue n-6/n-3 PUFA ratio (FAT-1+CPT-11/FO+CPT-11 samples). Each line connects the host and microbial data from one sample. One end of each connecting line for an observation indicates the host (differently colored to indicate the groups), and another end (dark yellow) indicates the gut microbiota (GM). (D) Principal component analysis (PCA) of the host and gut microbiome (genus-level) data associated with a high n-6/n-3 ratio and a low n-6/n-3 PUFA ratio. (E,F) Biomarker analysis using multivariate [Random Forests (RF) classification with PLS-DA feature ranking method] receiver operator characteristic curve (ROC) based exploratory analysis performed on the combined host and microbial parameters. (G) Post-CPT-11 cecal contents beta-glucuronidase (GUSB) activity measurements were associated with a high n-6/n-3 ratio and a low n-6/n-3 PUFA ratio. (H) ROC curve generated with classical univariate ROC curve analysis showing the sensitivity and specificity for cecal contents GUSB activity. Data are shown as mean ± standard error of the mean. *** p < 0.001, nonparametric Mann–Whitney test.