Gut bacteriophage dynamics during fecal microbial transplantation in subjects with metabolic syndrome

Abstract

Metabolic Syndrome (MetS) is a growing public health concern worldwide. Individuals with MetS have an increased risk for cardiovascular (CV) disease and type 2 diabetes (T2D). These diseases - in part preventable with the treatment of MetS - increase the chances of premature death and pose a great economic burden to health systems. A healthy gut microbiota is associated with a reduction in MetS, T2D, and CV disease. Treatment of MetS with fecal microbiota transplantation (FMT) can be effective, however, its success rate is intermediate and difficult to predict. Because bacteriophages significantly affect the microbiota membership and function, the aim of this pilot study was to explore the dynamics of the gut bacteriophage community after FMT in MetS subjects. We performed a longitudinal study of stool bacteriophages from healthy donors and MetS subjects before and after FMT treatment. Subjects were assigned to either a control group (self-stool transplant, n = 3) or a treatment group (healthy-donor-stool transplant; n-recipients = 6, n-donors = 5). Stool samples were collected over an 18-week period and bacteriophage-like particles were purified and sequenced. We found that FMT from healthy donors significantly alters the gut bacteriophage community. Subjects with better clinical outcome clustered closer to the heathy donor group, suggesting that throughout the treatment, their bacteriophage community was more similar to healthy donors. Finally, we identified bacteriophage groups that could explain these differences and we examined their prevalence in individuals from a larger cohort of MetS FMT trial.Trial information- http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2705; NTR 2705.

Keywords: Gut microbiome bacteriophages; fecal microbial transplant; human gut phage metagenomics; metabolic syndrome.

Figure 1.

Changes in the viral community of MetS subjects after FMT. (a) Schematic representation of the composition of the viral community before and after FMT in recipients from the treatment group (top panel) and the control group (bottom panel). Individuals in the treatment group received the stool microbial community of a healthy donor (n=6). Individuals in the control group received their own stool microbial community (n=3). (b) Bar plots of the community structure after FMT in MetS subjects. Plots represent the cumulative relative abundance of the different viral categories in each individual at each timepoint (Before FMT treatment- W0 and after- W3, 6, 12, 18). (c, d, e) Changes through time in the different viral categories. The treatment group was further divided in responders (n=3) or non-responders (n=3) based on treatment outcome. Significance was determined through a mixed effect model to account for repeated measures and missing data points followed by Sidak’s multiple comparison test. Asterisks show adjusted p-values: * <0.05, **<0.005, ***<0.0005

Figure 2.

Transfer and establishment of donor-invading viruses after FMT in the recipients gut viral community. (a) Cumulative relative abundance occupied by donor-invading bacteriophages. (b) Number of viruses (v) and their cumulative relative abundance (a) found in donors and recipients at each time point before and after FMT. C) Heatmaps of invading HV groups that take more than 0.05% of the community in at least one time point

Figure 3.

Analysis of donor-like HV viruses dynamics during the FMT time course. (a) Heatmap representation of log10 raw abundance of the 232 HV viruses that were shared between at least one healthy-donor recipient pair. Columns are organized based on average hierarchical clustering of Bray-Curtis dissimilarity and rows are organized based on complete hierarchical clustering of Euclidean distance. (b) Principal Coordinate Analysis of Bray-Curtis dissimilarity index of raw abundances of shared HV groups. Points represent individual time points. Number on top of the point represents week within the FMT course. (c) Bray-Curtis dissimilarities between healthy donors and their respective recipients

Figure 4.

Identification of phage groups enriched in treatment outcome subgroups. (a) Heatmap representation of log10 raw abundance of the HV viruses that significantly contribute to separate treatment groups in the ordination space in Figure 4b (simper analysis with 1000 permutations, p-value <0.05). Columns are organized based on average hierarchical clustering of Bray-Curtis dissimilarity and rows are organized based on complete hierarchical clustering of Euclidean distance. (b) Detection of these HV groups in study subjects pre-FMT using a q-PCR based assay. C) Percentage increase in glucose disappearance rate (Rd) from study subjects in this pilot study. The value of one control individual was removed (See statistical analysis). D) Correlation analysis between phage enriched in responder groups and the increase in Rd rate in subjects six weeks after transplant

Figure 5.

Prevalence of bacteriophages enriched in responder subjects in this study among a larger set of MetS subjects before FMT treatment. (a) HV abundance in cellular DNA extracted from stool samples of treatment subjects in Koote et al. FMT trial determined through q-PCR analysis. (b) ROC curves analysis of HV abundances pre-FMT. The area under the curve and its correspondent p-value determine the suitability for these HV groups to be used as predictors for treatment outcome