Bacterial Diversity of Intestinal Microbiota in Patients with Substance Use Disorders Revealed by 16S rRNA Gene Deep Sequencing

Abstract

Substance abuse and addiction are worldwide concerns. In China, populated with over 1.3 billion people, emerging studies show a steady increase in substance abuse and substance-related problems. Some of the major challenges include a lack of an effective evaluation platform to determine the health status of substance-addicted subjects. It is known that the intestinal microbiota is associated to the occurrence and development of human diseases. However, the changes of bacterial diversity of intestinal microbiota in substance-addicted subjects have not been clearly characterized. Herein, we examined the composition and diversity of intestinal microbiota in 45 patients with substance use disorders (SUDs) and in 48 healthy controls (HCs). The results show that the observed species diversity index and the abundance of Thauera, Paracoccus, and Prevotella are significantly higher in SUDs compared to HCs. The functional diversity of the putative metagenomes analysis reveals that pathways including translation, DNA replication and repair, and cell growth and death are over-represented while cellular processes and signaling, and metabolism are under-represented in SUDs. Overall, the analyses show that there seem to be changes in the microbiota that are associated with substance use across an array of SUDs, providing fundamental knowledge for future research in substance-addiction assessment tests.

Figure 1

Analysis of alpha diversity in HC (blue) vs SUDs (orange) predicted diversity by Chao 1 estimator (A), p = 0.11 and observed species (B), p = 0.03. Beta diversity measures in SUDs vs HCs. (C) Hot map was performed basing on the unweighted-unifrac distances matrix using the R package “vegan”, orange for the SUDs and blue for the HCs. (D) Principal Coordinate Analysis (PCoA) and UPGMA tree of unweighted-unifrac distances of samples, blue for the HCs and red for the SUDs (adonis test, R2 = 0.067, Pr (>F) = 0.001).

Figure 2

Genus-level taxonomic distribution of intestinal microbiota and top 20 genera in (A) 45 SUDs vs 48 HCs, (B) 29 age-matched SUDs vs 28 age-matched HCs, and (C) long-term SUDs vs short-term SUDs. Stacked columns for each of the group show the mean of abundance of a given genus as a percentage of the total bacterial sequences in the corresponding group.

Figure 3

Three-group shared bacteria in the VENN. Bacteria from Bacteroides, and Haemophilus (A) were consistently less abundant whereas the number of bacteria from Prevotella, Phascolarctobacterium and Ruminococcus (B) were consistently increased in SUDs vs HCs, and in long-term SUDs vs short-term SUDs.

Figure 4

Taxonomic biomarkers. (A) Linear discriminative analysis (LDA) effect size LEfSe analysis between the HCs (red) and SUDs (green). (B) Cardiogram showing differentially abundant taxonomic clades with an LDA score > 2.0 among cases and controls, p < 0.05.

Figure 5

Scatterplots of bacterial taxa indicative of SUDs. HC samples are shown as green dots and samples from SUDs are shown as red dots. p-values were calculated using the Mann-Whitney test (A) for 93 samples analysis, while (B) had 57 samples analysis.

Figure 6

Compare the difference notability function in KEGG module prediction using 16S data with PICRUSt.