Compositional and Functional Adaptations of Intestinal Microbiota and Related Metabolites in CKD Patients Receiving Dietary Protein Restriction

I-Wen Wu, Chin-Chan Lee, Heng-Jung Hsu, Chiao-Yin Sun, Yuen-Chan Chen, Kai-Jie Yang, Chi-Wei Yang, Wen-Hun Chung, Hsin-Chih Lai, Lun-Ching Chang, Shih-Chi Su, I-Wen Wu, Chin-Chan Lee, Heng-Jung Hsu, Chiao-Yin Sun, Yuen-Chan Chen, Kai-Jie Yang, Chi-Wei Yang, Wen-Hun Chung, Hsin-Chih Lai, Lun-Ching Chang, Shih-Chi Su

Abstract

The relationship between change of gut microbiota and host serum metabolomics associated with low protein diet (LPD) has been unraveled incompletely in CKD patients. Fecal 16S rRNA gene sequencing and serum metabolomics profiling were performed. We reported significant changes in the β-diversity of gut microbiota in CKD patients having LPD (CKD-LPD, n = 16). We identified 19 genera and 12 species with significant differences in their relative abundance among CKD-LPD patients compared to patients receiving normal protein diet (CKD-NPD, n = 27) or non-CKD controls (n = 34), respectively. CKD-LPD had a significant decrease in the abundance of many butyrate-producing bacteria (family Lachnospiraceae and Bacteroidaceae) associated with enrichment of functional module of butanoate metabolism, leading to concomitant reduction in serum levels of SCFA (acetic, heptanoic and nonanoic acid). A secondary bile acid, glyco λ-muricholic acid, was significantly increased in CKD-LPD patients. Serum levels of indoxyl sulfate and p-cresyl sulfate did not differ among groups. The relationship between abundances of microbes and metabolites remained significant in subset of resampling subjects of comparable characteristics. Enrichment of bacterial gene markers related to D-alanine, ketone bodies and glutathione metabolism was noted in CKD-LPD patients. Our analyses reveal signatures and functions of gut microbiota to adapt dietary protein restriction in renal patients.

Keywords: bile acids; chronic kidney disease; gut microbiome; low protein diet; short-chain fatty acids; uremic solute.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparisons of gut microbiota composition and diversity in non-CKD controls and CKD patients receiving LPD or NPD. (A) The distribution of top 10 phyla and top 10 genera (B) detected among groups. (C) α- diversity (Chao 1) and (D) β-diversity (Bray–Curtis similarity index) of gut microbial communities among groups. The box-plot shows the median, the 25th, and the 75th percentile in each group. *, p < 0.001 (E) Nonmetric multidimensional scaling (NMDS) ordination based on weighted UniFrac parameters of intestinal microbial communities among groups. Significant sample-to-sample dissimilarities refer to analysis of similarity (ANOSIM, p = 0.01) test for discrimination in community composition among groups. (F) Bacterial taxa that best characterize each group were determine by applying linear discriminant analysis of effect size (LEfSe) on OTU tables. LP, low protein diet; NP, normal-protein diet.
Figure 2
Figure 2
Changes in circulating metabolite concentration associated with LPD in CKD patients. Levels of metabolites among different groups were analyzed by Wilcoxon rank sum test. The box-plot shows the median, the 25th, and the 75th percentile in each group. *, p < 0.05. LPD, low protein diet; NPD, normal-protein diet; CKD, chronic kidney disease; glyco-λ-MCA, glyco-λ-muricholic acid; IS, indoxyl sulfate; pCS, p cresyl-sulfate.
Figure 3
Figure 3
Prediction of microbial gene functions among groups. (A) Pathway enrichment for KEGG metabolism was inferred by PICRUSt. Differences in relative abundance of predicted microbial genes related to the metabolism among groups. (B) Changes of specific pathway modules associated with LP in CKD patients. Differences in relative abundances of predicted microbial genes among LP vs. NP were analyzed using Student’s t test. *, p < 0.05; **, p < 0.01; ***, p < 0.001. LP, low protein diet; NP, normal-protein diet; CKD, chronic kidney disease.

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