Assessing the change of community spatial heterogeneity associated with IBD

Table 1 listed the parameters of Type-I and Type-III PLEs fitted to the three treatments (i.e., healthy, CD and UC), respectively. In the case of Type-I PLE, the parameter b for the healthy treatment is slightly larger than that of the other two treatments (Fig. 1). However, the differences among three treatments in terms of Type-III PLE seemed insignificant (Fig. 2). The Type-I PLE model suggests that IBD may have certain influence on the community spatial heterogeneity, but not on the spatial heterogeneity of mixed species populations. In other words, IBD may influence the community-level spatial heterogeneity, but not the mixed-species level heterogeneity. The former represents the inter-species abundance variations (heterogeneities) exhibited at the community level. The latter represents the population abundance variations (heterogeneities) among spatial sites in terms of the mixed species, which is essentially a species (population) entity or exhibited at the population level.

Table 1 Test results of fitting to Type-I and Type-III PLE for the healthy, CD and UC treatments. Full size table

Figure 1 Fitting to the Type-I PLE for the healthy, CD and UC treatments, respectively: the CD & UC treatments showed higher scaling parameter b. The X-axis represents the logarithm transform of m s , the mean species population size (abundance) per species in the community at a specific sampling site, and the Y-axis represents the logarithm transform of V s , the corresponding variance. The trend lines of scatter plots for the healthy, CD and UC treatments are in red with triangles, black with circles and green with squares respectively. Full size image

Figure 2 Fitting to the Type-III PLE for the healthy, CD and UC treatments, respectively: no significant differences between the three treatments. The X-axis represents the logarithm transform of m m , the mean of population abundances of a specific bacterial species across a series of spatial sites (per site), and the Y-axis represents the logarithm transform of V m , the corresponding variance. The trend lines of scatter plots for the healthy, CD and UC treatments are in red with triangles, black with circles and green with squares respectively. Full size image

Assessing the change of community neutrality associated with IBD

For each sample we calculated the fundamental biodiversity parameter θ, the immigration rate m and the corresponding likelihood using Etienne formula. Detailed results were listed in the Supplementary Table S1. We compared the likelihood (P 0 ) of observed dataset and the average likelihood (Ps) of corresponding 100 artificial datasets for each sample via Etienne formula. About 4.1% (3/74) samples in total satisfied the neutral prediction, and there were around 5.6% (1/18) samples in the healthy, 0% (0/18) in CD and 5.3%(2/38) in UC treatment satisfied the neutral prediction. No significant differences among the three treatments were observed. The parameters for all samples passing the neutrality test were listed in Table 2. Figure 3 showed the graphs of four samples fitting to the neutral theory model. In addition, we also tested 12 healthy communities that were first reported in Halfvarson et al.44, and all communities failed to pass the neutral test. The detail information of supplementary results was listed in Table S1.

Table 2 The parameters of the three samples that passed the neutrality test. Full size table

Figure 3 The graphs of four community samples fitted to the neutral theory model of biodiversity. The graphs show poor fitting of the neutral theory model, i.e., the significant difference between the actual community observations (red line) with the artificially simulated communities (black lines) based on the neutral theory model. Full size image

Then we compared the diversity parameters θ among 3 treatments. The means of θ are 71.43 (95%CI: 54.58–88.28) for the health, 84.59 (95%CI: 72.13–97.05) for CD and 52.29 (95%CI: 43.01–61.57) for UC treatment and the results were showed in Fig. 4. Significant differences were found among 3 treatments via variance analysis (p < 0.01). In the Bonferroni pair-wise comparison, the mean diversity index for CD was significantly higher than UC treatment (p < 0.01) and no significant differences were found between the other pairs.

Figure 4 The box plot of the fundamental diversity number (θ) in the three treatments (the healthy, CD and UC). The analysis of variance was used to compare the average θ value of the three treatments. With the Bonferroni pair-wise comparison, the CD treatment exhibited significant higher θ than the UC treatment (p < 0.01), but no significant differences were detected in the pairs of CD vs. the healthy and UC vs. the healthy. Full size image

Several previous studies have reported significant ecological changes of gut microbiota in IBD patients, compared with the healthy individuals. Our study confirmed that IBD is related to the change of gut microbiota diversity as demonstrated by the fundamental diversity number (θ) (Fig. 4). We found that the CD treatment showed significant higher biodiversity in gut microbiota that UC treatment. Although CD and UC shared some clinical attributes, they are genetically and fundamentally distinct disease processes45. Typically, CD is considered as a systemic disease with a long premorbid phase, where the inflammation could affect any part of the gut, whereas UC is a mucosal disease with an acute onset, often limited to distal colonic tract45,46. The compositional difference of gut microbiota between CD and UC patients has been found by previous study47. Up to date, though the pathogenesis of IBD has not been fully understood, it has been reported that the loss of protective bacteria and increase in detrimental bacteria occur concomitantly47, which may be an important driver for IBD. In the gut microbiota of CD patient, the invasion of harmful bacteria may be the domination factor due to wider scope of inflammation, while in UC patient, the loss of beneficial bacteria may overwhelm the invading bacteria, which may be one explains that CD treatment show significant higher biodiversity that UC treatment.

A series of external factors that influence the gut microbiota are found associated with IBD, for example, larger family size, early life exposure to pets and farm animals, and greater number of siblings are found to increase the risk of IBD, while breastfeeding seems to be protective9. These factors may affect, though via different ways, the micro-ecosystem of gut, and lead to ecological changes in the gut microbiota. To date, much of the ecological changes associated with IBD have been focused on the composition and diversity of gut microbial communities. The dual objective of our study is to expand existing studies from two aspects. Our first objective is to determine if the spatial heterogeneity of gut microbiota would be changed due to IBD by applying the extended power law models. Our second objective is to investigate whether or not IBD will change the assembly mechanism of gut microbiota by applying the neutral theory.

Regarding our first objective, although previous studies have reported the presence of high inter-individual variations of gut microbiota within humans, the alteration of degree of such variations (i.e., spatial heterogeneity) associated with IBD has not been quantified yet. The original Taylor’s (1961) power law26 is a powerful tool to measure both the spatial and temporal heterogeneities of population, and the extended power law models (i.e., PLEs) by Ma (2015)27 are able to assess the heterogeneity at the community level or mixed-specie level. Our study revealed that the Type-I PLE heterogeneity in the healthy treatment is slightly higher than that in the CD and UC treatments. Type-I PLE represents the inter-species heterogeneity, and higher degree of inter-species heterogeneity implies greater differences among species, suggesting higher possibility of the presence of dominant species, which may be a normal state in healthy human gut. We conjecture that the IBD disease (CD or UC) may reduce the abundances of dominant bacterial species and consequently lower the community spatial heterogeneity. Type-III PLE describes mixed-species heterogeneity. It reflects the degree of fluctuations of the abundance of all bacterial species across different samples (i.e. intra-species heterogeneity). Because its calculation considers the variance of all species in a set of communities, the changes in several specific species may not cause significant alternation of the intra-species heterogeneity or in another situation, the influence to intra-species heterogeneity caused by the decrease of some species may be compensated by the increase of some other species. The Type-III PLE heterogeneity did not display significant differences among the 3 treatments, suggesting that IBD is not associated with the change of intra-species heterogeneity. The reason may be that IBD could affect only a few certain bacterial species, and such influence is not significant enough to alert the overall intra-species heterogeneity of gut microbiota as there are usually thousands species in gut microbiota. And the loss of beneficial bacteria and acquisition of detrimental bacteria are two opposite processes that may occur parallelly in the gut microbiota of IBD (both UC and CD) patients, from which the influences affecting the intra-species heterogeneity may cancels each other out in some extend.

A number of studies have demonstrated the compositional differences of gut microbiota in IBD patients compared with healthy individuals48. As with many ecologists, the gut microbiota is essentially a highly complex community that has little fundamental difference with other ecological communities in nature environment. Hence the ecological theories traditionally developed in the macro-ecology of plants and animals should also be appropriate in micro-ecology area. One of the core topics in community ecology is the mechanism of community assembly and diversity maintenance. However, to the best of our knowledge, the question of whether the ecological force that shapes gut microbiota is related to IBD is still poorly understood. Therefore our second objective in this study is to make efforts to answer this question. We applied Hubbell’s neutral theory for biodiversity to test the neutrality of the observed samples in both IBD patients and healthy individuals. We found that only 4.1% (3/74) community samples satisfied the prediction of the neutral theory, and no significant differences in terms of the passing rate were detected among the three treatments. For this result, we suggest that the assembly and diversity maintenance of gut microbial communities are mostly determined by niche differentiations, and IBD may not significantly influence the assembly mechanism and diversity maintenance of gut microbial communities.

There are two main limitations in our study: (i) In previous study, it has been demonstrated that the composition of gut microbiota is different in different parts of gut28. Therefore the stool sample may not be the best type for characterizing IBD associated gut microbiota, as it could serve as a pool where the bacteria species come from different parts of gut. Further study should also try to use mucosal sample in the same position across samples to perform parallel comparison. (ii) It has been proven that IBD-associated gut microbiota is dynamic44. Our study, just like many other studies, used a cross-sectional dataset in a single time point, from which the result may biased due to temporal variance. Further study should make efforts to collect enough time-series datasets and use temporal model to investigate diseases-related ecological changes in gut microbiota.