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. 2010 Oct;20(10):1411-9.
doi: 10.1101/gr.107987.110. Epub 2010 Aug 24.

Reshaping the gut microbiome with bacterial transplantation and antibiotic intake

Affiliations

Reshaping the gut microbiome with bacterial transplantation and antibiotic intake

Chaysavanh Manichanh et al. Genome Res. 2010 Oct.

Abstract

The intestinal microbiota consists of over 1000 species, which play key roles in gut physiology and homeostasis. Imbalances in the composition of this bacterial community can lead to transient intestinal dysfunctions and chronic disease states. Understanding how to manipulate this ecosystem is thus essential for treating many disorders. In this study, we took advantage of recently developed tools for deep sequencing and phylogenetic clustering to examine the long-term effects of exogenous microbiota transplantation combined with and without an antibiotic pretreatment. In our rat model, deep sequencing revealed an intestinal bacterial diversity exceeding that of the human gut by a factor of two to three. The transplantation produced a marked increase in the microbial diversity of the recipients, which stemmed from both capture of new phylotypes and increase in abundance of others. However, when transplantation was performed after antibiotic intake, the resulting state simply combined the reshaping effects of the individual treatments (including the reduced diversity from antibiotic treatment alone). Therefore, lowering the recipient bacterial load by antibiotic intake prior to transplantation did not increase establishment of the donor phylotypes, although some dominant lineages still transferred successfully. Remarkably, all of these effects were observed after 1 mo of treatment and persisted after 3 mo. Overall, our results indicate that the indigenous gut microbial composition is more plastic that previously anticipated. However, since antibiotic pretreatment counterintuitively interferes with the establishment of an exogenous community, such plasticity is likely conditioned more by the altered microbiome gut homeostasis caused by antibiotics than by the primary bacterial loss.

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Figures

Figure 1.
Figure 1.
Experimental design. Four groups of rats were used as recipients of different treatments: (C) controls; (A) ATB intake during 3 d; (T) transplantation; (AT) 3-d ATB intake followed by transplantation. The cecal content of four donor rats was pooled and transplanted to a recipient rat once by gavage. Fecal samples of all rats were collected at different time points, day 0 (D0), day 3 (D3), month 1 (M1), and month 3 (M3).
Figure 2.
Figure 2.
Variation of bacterial load and richness. (A) Number of observed phylotypes as defined at 97% sequence identity. For both figures, mean value (n = 3 for controls and ATB; n = 4 for Transplanted and ATB + Transplanted) ±SD are plotted. (B) Bacterial quantification assessed by real-time PCR of the 16S gene at three time points: baseline (D0), day 3 (D3), and month 3 (M3).
Figure 3.
Figure 3.
16S gene surveys show clustering of bacterial communities by treatments. (A) Principal coordinates analysis (PCoA) performed on pairwise unweighted UniFrac distances shows a 3-d antibiotic effect (PC1 and PC2) and a long-term effect for all treated groups (PC2 and PC3). (B) Hierarchical cluster tree built using UPGMA (unweighted pair group method with arithmetic mean) from the same UniFrac distance matrix that was used for the PCoA. Each dot represents a sample codified by either C (controls), A (ATB), T (Transplanted), or AT (ATB and Transplanted), followed by the number of the animals (from one to three or to four) in each group and by a date of sample collection (#D0, #D3, #W2 [week 2], #M1, and #M3). The effect of each treatment leads to five clusters of samples (I to V). Branches in the UPGMA tree are colored according to their jackknife support: red, 75%–100%; yellow, 50%–75%; green, 25%–50%; blue, <25% support.
Figure 4.
Figure 4.
Variation of the diversity of the microbial communities. Phylotypes were assigned a taxonomy using the RDP classifier at the phylum level and at different time points. Mean value (n = 3 for controls and ATB; n = 4 for Transplanted and ATB+Transplanted) ±SD are plotted.
Figure 5.
Figure 5.
Network plots of shared microbial diversity. The relationships between phylotypes and samples are represented as a bipartite graph in which nodes are either phylotypes (small) or samples (large), and connecting lines between small and large nodes mean that the phylotype was found in the given sample. Colors of lines and large nodes indicate the donor sample (blue), the sample before treatment (red), and the sample obtained 3 mo after treatment (green). The intensity (opacity) of each line reflects the relative abundance of each detected phylotype in a given sample; the groups of phylotypes that join any given pair of samples indicate the proportion of shared phylotypes, and the phylotypes connected to only a single sample are unique. The number of shared phylotypes between samples and phylotypes uniquely found in each sample is indicated. The panels represent the controls (C), effects of antibiotics only (A), transplantation only (T), or transplantation with antibiotics (AT). Intersections of red, blue, and green lines show common phylotypes between donor and recipient rats at any time-point.

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