糖尿病动物肠道内容物的代谢组成变化研究

Diabetes is a complex polygenic disease resulting from gene-environment interactions with possible consequences of multiple complications and premature mortality. The initiating mechanisms behind the development of diabetes are largely unknown and thus understandings of such mechanistic details are crucial for detection of the diabetes onset and for timely interventions. Symbiotic gut microbiota plays important roles in many aspects of mammalian physiology and thus in the hosts' health and diseases. Some early studies have demonstrated that intestinal microbiota is a causal factor in the development of this disease. And many gut microbiome-based studies involve sequence analysis of stool samples. The limitations of this approach are that it is not yet known which of the many hundreds of species are of "key" importance in host health, and little is understood of the molecular host-microbiome interactions that influence host metabolic pathways. And the end-product(i.e. stool) does not reflect the microbial-host interactions present within regions of the gut. So in this project, we will systematically analyze the metabolite compositions of T1DM and T2DM animal jejunal, ileal, cecal, colonic contents and feces using the newly developed NMR-based metabonomic strategy. And key metabolic pathways and biomarkers during diabetes processes will be elucidated by multivariate data analysis methods. We will then investigate gut microbiomic structures of the animal by using microbiomic stools such as PCR. Patterns of covariation are extracted by using multivariate statistical approaches to establish the association between host metabolism and variation of gut microbiota during diabetes processes. This project will provide baseline information for pathogenesis, early detection of the diabetes onset, and timely interventions. And this approach will allow identification of potentially important associations between changes of bacterial community structure and dynamics of host metabolic patterns that can be used to develop new and existing hypotheses on the relationships between dysbiosis and disease.

糖尿病是一种由遗传和环境等多因素共同作用引起的代谢性疾病，具有很高的发病率和死亡率，其病因至今尚未完全阐明。最近多个研究表明，肠道菌群与宿主糖尿病的发生发展有着密切联系。然而目前对于肠道菌群的了解大部分是基于对宿主粪便样本微生物群落结构的研究，对于肠道菌群影响宿主的代谢通路分析甚少，并且单一的研究对象（粪样）也无法全面的反应肠道菌群和宿主的相互作用。因此，本项目将在发展以NMR为基础的代谢组分析方法上，获得糖尿病模型动物的空肠、回肠、盲肠和结肠内容物以及粪样的代谢组成特征，并结合多变量统计学方法来研究糖尿病发生发展过程中肠道内容物的代谢变化规律和关键代谢标志物，然后通过定量PCR等分子检测手段并结合统计学方法确定肠道菌群结构的改变与宿主代谢通路的共变化特征。本项目的顺利完成将为糖尿病的预防和治疗提供基础数据，并为了解肠道菌群对宿主健康及疾病的影响提供一种新的思路和分析方法。

糖尿病是一种由遗传和环境等多因素共同作用引起的代谢性疾病，具有很高的发病率和死亡率，其病因至今尚未完全阐明。最近多个研究表明，肠道菌群与宿主糖尿病的发生发展有着密切联系。然而目前对于肠道菌群的了解大部分是基于对宿主粪便样本微生物群落结构的研究，对于肠道菌群影响宿主的代谢通路分析甚少，并且单一的研究对象（粪样）也无法全面的反应肠道菌群和宿主的相互作用。因此，我们首先使用1H NMR研究糖尿病模型动物的空肠、回肠、盲肠和结肠内容物以及粪样的代谢组成特征，并结合多变量统计学方法来研究糖尿病动物肠道内容物的代谢变化规律和关键代谢标志物，然后通过16S rRNAS基因测序检测手段并结合统计学方法确定肠道菌群结构的改变与宿主代谢通路的共变化特征。这些结果为糖尿病的预防和治疗提供基础数据，并为了解肠道菌群对宿主健康及疾病的影响提供一种新的思路和分析方法。