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. 2017 Feb 13:2:17004.
doi: 10.1038/nmicrobiol.2017.4.

Dynamics of the human gut microbiome in inflammatory bowel disease (V体育官网)

Jonas Halfvarson  1 , Colin J Brislawn  2 , Regina Lamendella  3 , Yoshiki Vázquez-Baeza  4 , William A Walters  5 , Lisa M Bramer  6 , Mauro D'Amato  7   8 , Ferdinando Bonfiglio  9 , Daniel McDonald  10 , Antonio Gonzalez  11 , Erin E McClure  3 , Mitchell F Dunklebarger  3 , Rob Knight  4   10   11 , Janet K Jansson  2
Affiliations

Dynamics of the human gut microbiome in inflammatory bowel disease

VSports在线直播 - Jonas Halfvarson et al. Nat Microbiol. .

Abstract

Inflammatory bowel disease (IBD) is characterized by flares of inflammation with a periodic need for increased medication and sometimes even surgery. The aetiology of IBD is partly attributed to a deregulated immune response to gut microbiome dysbiosis. Cross-sectional studies have revealed microbial signatures for different IBD subtypes, including ulcerative colitis, colonic Crohn's disease and ileal Crohn's disease. Although IBD is dynamic, microbiome studies have primarily focused on single time points or a few individuals. Here, we dissect the long-term dynamic behaviour of the gut microbiome in IBD and differentiate this from normal variation VSports手机版. Microbiomes of IBD subjects fluctuate more than those of healthy individuals, based on deviation from a newly defined healthy plane (HP). Ileal Crohn's disease subjects deviated most from the HP, especially subjects with surgical resection. Intriguingly, the microbiomes of some IBD subjects periodically visited the HP then deviated away from it. Inflammation was not directly correlated with distance to the healthy plane, but there was some correlation between observed dramatic fluctuations in the gut microbiome and intensified medication due to a flare of the disease. These results will help guide therapies that will redirect the gut microbiome towards a healthy state and maintain remission in IBD. .

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Defining a healthy plane
Diagram summarizing the procedure for creating a representative plane for a group of samples S: a, sample selection, b, model fitting and c, distance calculations for all samples. The healthy plane is then located in UniFrac space by d, fitting a line to the major axis of the points, and e, defining a least-squares fit to identify a plane that minimizes the sum of squares of distances to the nearest point on the plane. f, Verification that the position of the healthy plane is not driven by proteobacteria-dominated outliers: Procrustes Analysis comparing original samples and those with Proteobacteria removed. A vector connects each original sample (red) with the same samples after Proteobacteria have been omitted (black). p < 0.001, M2 = 0.018, 999 permutations. g, The short length of most vectors indicates that the relative composition of most samples does not change when proteobacteria are filtered out.
Figure 2
Figure 2. The gut microbiomes of different IBD subtypes display different distributions relative to a healthy plane (HP)
a, Median distances from HP for each IBD subtype. All IBD subtypes were significantly different from healthy controls (GLM, all p < 0.00261). b, UniFrac distances between subsequent samples. c, Distance to HP for each individual patient. HP was defined using data shown in Supplemental Video 1. See Supplementary Table 1 for composition of downstream analysis cohort. Boxes show interquartile range (IQR). Whiskers denote the lowest and highest values within 2.5 × IQR of the median. Circles represent outliers.
Figure 3
Figure 3. Correlation between fecal calprotectin concentrations and distance to a defined healthy plane (HP) in 3D ordination space
Data represent a correlation of f-calprotectin levels and distance to the here defined healthy plane in 3D ordination space (see Supplementary Video 1) for each individual and time point for different inflammatory bowel disease (IBD) subtypes. To compare the relationship between f-calprotectin and the healthy plane, a generalized linear mixed effects model was fit, with a conditional Gamma distribution, using f-calprotectin and disease type as fixed effects and including a random subject effect; f-calprotectin was not significant (p = 0.27501).
Figure 4
Figure 4. Microbiome dynamics of selected individuals from each IBD subtype and a healthy control
From each IBD subtype and healthy control group, representative individuals sampled over the most time points and having complete clinical and sequence data were selected. Data represent f-calprotectin values, distance to the healthy plane, and Shannon diversity and rarified abundances of most common taxa at the family level. Note that taxa unclassified at the family level are represented in the ‘f__’ category.
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References

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