菌群多样性与疾病关系的生态机制及病因研究

多样性指数的计算几乎是目前所有菌群研究的基本分析内容之一，但菌群多样性与疾病发生间的关系(Diversity-Disease Relationship, DDR)远比多数文献所揭示的复杂！申请人(Ma et al. 2019 The ISME Journal)通过严格统计检验发现：只有大约1/3的报道中，多样性才与疾病发生相关。故拟目标[1]: 进一步扩展对DDR关系的研究方法及疾病数据以求证其“1/3”DDR关系是否可靠。目标[2]:研究DDR关系的生态机制。拟通过中性理论、中性-生态位混合模型及复杂网络分析探索菌群、疾病、宿主间作用的生态机制。目标[3]:探究疾病DDR格局与病因(Etiology)的关系，病因研究所观察到的菌群失调(Dysbiosis)就是稳定性的破坏,故以“多样性-稳定性关系”为例求证(Ma＆Ellison 2019, Ecological Monographs)。

Diversity indexes such as species richness, Shannon entropy and Simpson index have been routinely computed in virtually every study of the human microbiome associated diseases (MADs) since the launch of the human microbiome project (HMP). However, the exact DDR patterns (disease associated with higher, lower or constant microbiome diversity) were not rigorously investigated until very recently (Ma et al. 2019, The ISME Journal), not to mention the ecological mechanisms underlying various DDR patterns. These two problems (DDR patterns and their underlying ecological mechanisms) constitute the first two objectives of the proposed study. An even more important problem, and also more challenging research topic is the relationship between the DDR and disease etiology of MADs, which constitutes the third objective of our proposal. ..Regarding objective No 1, in a recent meta-analysis with big data of MADs (Ma et al. 2019, The ISME Journal), we found that there is not a consistent DDR pattern, contrary to common perception in previous studies. We further investigate the DDR patterns by expanding the exploration to the two other aspects of diversity metrics, their inter-individual heterogeneity measured with the power law extension by Ma (2015), and their scaling over space and time with the so-termed DAR/DTR/DTAR, which are the extensions of classic SAR/STR/STAR (Ma 2018a, b) and offer powerful tools to sketch out the biogeography maps of the human microbiome. The objective-1 also investigates the shared species (analysis) between the healthy and diseased treatments, which can be utilized for diagnosis of MADs. ..Regarding objective No 2—the ecological mechanisms of the observed DDR patterns, we resort to the big-four process synthesis for modern community ecology and biogeography. The four processes (drift, selection, dispersal and speciation) are recognized as the fundamental mechanisms (processes) that shape the diversity patterns of biological communities and drive the community dynamics. We use the neutral theory of biodiversity and neutral-niche hybrid models to assess and interpret the relative significance of the three processes (drift, speciation and dispersal), and use network analysis to measure the selection—the inter-individual and inter-species differences in their fitness (adaptations) as well as the differences in their interactions with environments (hosts). Together, both the neutral theory of biodiversity and network analysis can effectively measure the relative significance of the four processes (mechanisms) as well as the disease effects on the processes. ..Regarding Objective No. 3—the implications or the relationships of DDR to clinical etiology of MADs, we expect that the relationships are too diverse to be fully investigated in our proposed study. For example, many of the MADs are mediated by immune system and the role of microbiomes is likely exerted through immune system, which is beyond the scope of our proposal. Given the enormous diversity and complexity, we limit our exploration for objective to one disease, bacterial vaginosis (BV). BV represents a category of MADs, where the loss of microbial community stability or the so-termed dysbiosis was found to play an important role. For this reason, we resort to the classic diversity-stability relationship (DSR), which is considered as one of the central topics of community ecology because stability or in the terminology of microbiome scientists, the dysbiosis, is essential for the normal functionality (services) of any ecosystem including the human microbiome. We will apply and further extend an important advance we recently made, i.e., species dominance network (SDN) (Ma & Ellison 2019, Ecological Monographs) to reach this objective.