Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury

Abstract

Drug induced liver injury (DILI) is a kind of liver dysfunction which caused by drugs, and gut microbiota could affect liver injury. However, the relationship between gut microbiota and its metabolites in DILI patients is not clear. The total gut microbiota DNA was extracted from 28 DILI patient and 28 healthy control volunteers (HC) and 16S rDNA gene were amplified. Next, differentially metabolites were screened. Finally, the correlations between the diagnostic strains and differentially metabolites were studied.The richness and uniformity of the bacterial communities decreased in DILI patients, and the structure of gut microbiota changed obviously. Enterococcus and Veillonella which belong to Firmicutes increased in DILI, and Blautia and Ralstonia which belong to Firmicutes, Dialister which belongs to Proteobacteria increased in HC. In addition, these diagnostic OTUs of DILI were associated with the DILI damage mechanism. On the other hands, there were 66 differentially metabolites between DILI and HC samples, and these metabolites were mainly enriched in pyrimidine metabolism and steroid hormone biosynthesis pathways. Furthermore, the collinear network map of the key microbiota-metabolites were constructed and the results indicated that Cortodoxone, Prostaglandin I1, Bioyclo Prostaglandin E2 and Anacardic acid were positively correlated with Blautia and Ralstonia, and negatively correlated with Veillonella.This study analyzed the changes of DILI from the perspective of gut microbiota and metabolites. Key strains and differentially metabolites of DILI were screened and the correlations between them were studied. This study further illustrated the mechanism of DILI.

Figure 1

Species diversity analysis. (A) Relative abundance curve of gut microbiota. Abscissa: OTU rank, representing OTU arranged according to abundance in the sample; Ordinate: The relative abundance of the number of sequences in this rank OTU is the number of sequences belonging to the OTU divided by the total number of sequences, green is HC, red is DILI. (B) Alpha-diversity indexes. (B1) Chao1 index; (B2) ACE index; (B3) observed species index; (B4) goods Coverage index.Abscissa: different groups, green is HC, red is DILI; Ordinate: diversity index value, where the upper left corner is p value display, p < 0.001: ***, p < 0.01: **, p ≤ 0.05: *(C) PCoA analysis. HC is shown in green and DILI in red, representing samples from different environments or conditions. The horizontal and vertical axes are relative distances and have no practical significance.

Figure 2

Analysis of the species composition diversity. (A) Relative proportion at the phylum in samples. The abscissa is samples of DILI and HC groups, the ordinate is the relative abundance, and different colors represent different phylum. (B) Different abundance of microbiota at the phylum between DILI and HC groups. The abscissa is the group, the ordinate is the relative abundance, and different colors represent different phylum. (C) Relative proportion at the genus in samples. The abscissa is samples of DILI and HC groups, the ordinate is the relative abundance, and different colors represent different genus. (D) Different abundance of microbiota at the genus between DILI and HC groups. The abscissa is the group, the ordinate is the relative abundance, and different colors represent different genus. (E) Cluster trees of LEfSE analysis. Red and green areas represent different samples. In the tree, the red nodes represent the important microbiota in DILI, the green nodes represent the microbial groups that played an important role in the HC group, and the yellow nodes are the microbial groups that did not play an important role in the two groups. In the legend on the right, the English letters in the figure are the species names. The circles from inside to outside in the branching diagram are the classification level from phylum to species. The diameter of each small circle is proportional to the relative abundance in the gut microbiota, and the letters p, c, o, f, g and s represent phylum, class, order, family, genus and species, respectively. (F) Histogram of LDA analysis. LDA score was used to screen the differential microbiota. The microbial taxa with significant effects in the two samples are LDA score on the abscissa and differential microbiota on the ordinate.

Figure 3

Analysis of the diagnostic OTUs of DILI. (A) The ROC curves of 5 characteristic strains (at the genus level). (A1) The ROC curves of Blautia; (A2) The ROC curves of Ralstonia; (A3) The ROC curves of Dialister; (A4) The ROC curves of Enterococcus; (A5) The ROC curves of Veillohella. (B) The functional prediction of the 19 diagnostic strains. The abscissa is the mean relative abundance of each group, and the ordinate is the pathway name.

Figure 4

Analysis of the differentially metabolites. (A) The PLS-DA model. (A1) PLS-DA model. The abscissa and ordinate are the sample scores in the first two axes of PCA, that is, the sorting coordinates of each sample in PC1 and PC2 axes, according to which the differences in metabolite composition of each sample can be evaluated. Green is the DILI group, and orange is the HC group; (A2) Permutation test plot of PLS-DA model. The abscismal is the correlation coefficient between the original data and the replacement data, the ordinate is the R2Y value and Q2 value, the red point is the Q2 value, the green point is the R2Y value, the red line is the regression line of Q2, the green is the regression line of R2Y, the rightmost is the true value, and the left is the simulated value. (B) Volcano map of metabolites in samples. The abscission is log10 (p value), and the ordinate represents the log2(fold change). Each point in the figure represents a metabolite; red represents up-regulated differential genes, blue represents down-regulated differential metabolites, and gray represents non-significantly differential metabolites. (C) Heatmap of differentially metabolites.Each small square represents each differential metabolite, and its color indicates the amount of the differential metabolite. The higher the value, the darker the color (Red is high expression, and blue is low expression). (D) The functional prediction of different metabolites. The horizontal axis represents log10(p value) and the vertical axis represents enrichment pathways. Each dot in the figure represents an enrichment pathway, the lighter the color, the greater the p value, and the larger the dot, the greater the proportion of enrichment.

Figure 5

Correlation analysis of the microbiota and the metabolites. (A) The correlation between the differentially metabolites and diagnostic strains. The abscissa is the differential microbiota, the ordinate is the differential metabolites, each small cell represents the similarity, the more red color represents the stronger positive correlation, and the more blue color represents the stronger negative correlation. (B) The collinear network map of the key microbiota-metabolites. Pink dots are genus differential microbiota, blue dots are correlated differential metabolites, gray lines represent negative correlation, and yellow lines represent positive correlation.