A comprehensive diversity analysis on the gut microbiomes of ASD patients: from alpha, beta to gamma diversities.

Autism spectrum disorder (ASD) is estimated to influence as many as 1% children worldwide, but its etiology is still unclear. It has been suggested that gut microbiomes play an important role in regulating abnormal behaviors associated with ASD. A de facto standard analysis on the microbiome-associated diseases has been diversity analysis, and nevertheless, existing studies on ASD-microbiome relationship have not produced a consensus. Here, we perform a comprehensive analysis of the diversity changes associated with ASD involving alpha-, beta-, and gamma-diversity metrics, based on 8 published data sets consisting of 898 ASD samples and 467 healthy controls (HC) from 16S-rRNA sequencing. Our findings include: (i) In terms of alpha-diversity, in approximately 1/3 of the studies cases, ASD patients exhibited significantly higher alpha-diversity than the HC, which seems to be consistent with the "1/3 conjecture" of diversity-disease relationship (DDR). (ii) In terms of beta-diversity, the AKP (Anna Karenina principle) that predict all healthy microbiomes should be similar, and every diseased microbiome should be dissimilar in its own way seems to be true in approximately 1/2 to 3/4 studies cases. (iii) In terms of gamma-diversity, the DAR (diversity-area relationship) modeling suggests that ASD patients seem to have large diversity-area scaling parameter than the HC, which is consistent with the AKP results. However, the MAD (maximum accrual diversity) and RIP (ratio of individual to population diversity) parameters did not suggest significant differences between ASD patients and HC. Throughout the study, we adopted Hill numbers to measure diversity, which stratified the diversity measures in terms of the rarity-commonness-dominance spectrum. It appears that the differences between ASD patients and HC are more propounding on rare-species side than on dominant-species side. Finally, we discuss the apparent inconsistent diversity-ASD relationships among different case studies and postulate that the relationships are not monotonic.

Further Quantifying the Niche-Neutral Continuum of Human Digestive Tract Microbiomes with Near Neutral Model and Stochasticity Analysis.

It is postulated that the human digestive tract (DT) from mouth to intestine is differentiated into diverse niches. For example, Segata et al. discovered that the microbiomes of diverse habitats along the DT could be distinguished as 4 types (niches) including (i) stool; (ii) sub-gingival plaques (SubP) and supra-gingival plaques (SupP); (iii) tongue dorsum (TD), throat (TH), palatine tonsils (PT), and saliva (Sal); and (iv) hard palate (HP) and buccal mucosa (BM), and keratinized gingiva (KG). These niches are different not only in composition, but also in metabolic potentials. In a previous study, we applied Harris et al's multi-site neutral and Tang and Zhou's niche-neutral hybrid models to characterize the DT niches discovered by Segata et al. Here, we complement the previous study by applying Sloan's near-neural model and Ning et al's stochasticity analysis framework to quantify the niche-neutral continuum of the DT microbiome distribution to shed light on the possible ecological/evolutionary mechanism that shapes the continuum. Overall but excluding the stool site, the proportion of neutral OTUs (46%) is slightly higher than that of the positive selection (38%), but significantly higher than negative selection (15%). The gut (stool) exhibited 3 to 12 times lower neutrality than other DT sites. The analysis also cross-verified our previous hypothesis that the KG (keratinized gingiva) is of distinct assembly dynamics in the DT microbiome, should be treated as a fifth niche. Our findings offer new insight on the long-standing debate concerning whether a minimum of 2-mm of KG width is necessary for marginal periodontal health.

Niche-Neutral Continuum Seems to Explain the Global Niche Differentiation and Local Drift of the Human Digestive Tract Microbiome.

The human digestive tract (DT) is differentiated into diverse niches and harbors the greatest microbiome diversity of our bodies. Segata et al. (2012) found that the microbiome of diverse habitats along the DT may be classified as four categories or niches with different microbial compositions and metabolic potentials. Nonetheless, few studies have offered theoretical interpretations of the observed patterns, not to mention quantitative mechanistic parameters. Such parameters should capture the essence of the fundamental processes that shape the microbiome distribution, beyond simple ecological metrics such as diversity or composition descriptors, which only capture the manifestations of the mechanisms. Here, we aim to get educated guesses for such parameters by adopting an integrated approach with multisite neutral (MSN) and niche-neutral hybrid (NNH) modeling, via reanalyzing Segata's 16s-rRNA samples covering 10 DT-sites from over 200 healthy individuals. We evaluate the relative importance of the four essential processes (drift, dispersal, speciation, and selection) in shaping the microbiome distribution and dynamics along DT, which are assumed to form a niche-neutral continuum. Furthermore, the continuum seems to be hierarchical: the selection or niche differentiations seem to play a predominant role (> 90% based on NNH) at the global (the DT metacommunity) level, but the neutral drifts seem to be prevalent (> 90% based on MSN/NNH) at the local sites except for the gut site. An additional finding is that the DT appears to have a fifth niche for the DT microbiome, namely, Keratinized gingival (KG), while in Segata's original study, only four niches were identified. Specifically, in Segata's study, KG was classified into the same niche type including buccal mucosa (BM), hard palate (HP), and KG. However, it should be emphasized that the proposal of the fifth niche of KG requires additional verification in the future studies.

Diversity Scaling Analysis of Chinese Gut Microbiomes Across Ethnicities and Lifestyles.

Diversity scaling (changes) of human gut microbiome is important because it measures the inter-individual heterogeneity of diversity and other important parameters of population-level diversity. Understanding the heterogeneity of microbial diversity can be used as a reference for the personalized medicine of microbiome-associated diseases. Similar to diversity per se, diversity scaling may also be influenced by host factors, especially lifestyles and ethnicities. Nevertheless, this important topic regarding Chinese populations has not been addressed, to our best knowledge. Here, we fill the gap by applying a recent extension to the classic species-area relationship (SAR), i.e., diversity-area relationship (DAR), to reanalyze a large dataset of Chinese gut microbiomes covering the seven biggest Chinese ethnic groups (covering > 95% Chinese) living rural and urban lifestyles. Four DAR profiles were constructed to investigate the diversity scaling, diversity overlap, potential maximal diversity, and the ratio of local to global diversity of Chinese gut microbiomes. We discovered the following: (i) The diversity scaling parameters (z) at various taxon levels are little affected by either ethnicity or lifestyles, as exhibited by less than 0.5% differences in pairwise comparisons. (ii) The maximal accrual diversity (potential diversity) exhibited difference in only about 5% of pairwise comparisons, and all of the differences occurred in ethnicity comparisons (i.e., lifestyles had no effects). (iii) Ethnicity seems to have stronger effects than lifestyles across all taxon levels, and this may reflect the reality that China has been experiencing rapid urbanization in the last few decades, while the ethnic-related genetic background may change relatively little during the same period.

Diversity Scaling of Human Digestive Tract (DT) Microbiomes: The Intra-DT and Inter-individual Patterns.

The human gut microbiome has been extensively studied, but its diversity scaling (changes or heterogeneities) along the digestive tract (DT) as well as their inter-individual heterogeneities have not been adequately addressed to the best of our knowledge. Here we fill the gap by applying the diversity-area relationship (DAR), a recent extension to the classic species-area relationship (SAR) in biogeography, by reanalyzing a dataset of over 2000 16s-rRNA microbiome samples obtained from 10 DT sites of over 200 individuals. We sketched out the biogeography "maps" for each of the 10 DT sites by cross-individual DAR analysis, and the intra-DT distribution pattern by cross-DT-site DAR analysis. Regarding the inter-individual biogeography, it was found that all DT sites have the invariant (constant) scaling parameter-all sites possessing the same diversity change rate across individuals, but most sites have different potential diversities, which include the portions of diversity that may be absent locally but present regionally. In the case of this study, the potential diversity of each DT site covers the total diversity of the respective site from all individuals in the cohort. In terms of the genus richness, an average individual hosts approximately 20% of the population-level genus richness (total bacterial genus of a human population). In contrast, in terms of community biodiversity, the percentages of individual over population may exceed 90%. This suggests that the differences between individuals in their DT microbiomes are predominantly in the composition of bacterial species, rather than how their abundances are distributed (i.e., biodiversity). Regarding the intra-DT patterns, the scaling parameter (z) is larger-suggesting that the intra-DT biodiversity changes are larger than inter-individual changes. The higher intra-DT heterogeneity of bacteria diversity, as suggested by larger intra-DT z than the inter-individual heterogeneity, should be expected since the intra-DT heterogeneity reflects the functional differentiations of the DT tract, while the inter-individual heterogeneity (z) reflects the difference of the same DT site across individuals. On average, each DT site contains 21-36% of the genus diversity of the whole DT, and the percentages are even higher in terms of higher taxon levels.