赵立平:菌株水平分析,了解菌群与疾病关系的正道

基因和代谢组技术促进菌株水平分析:
新算法可在宏基因组数据中组装特定菌株基因组草图;
以核磁共振为基础的代谢组分析,可在尿液等样本鉴定出与疾病表型相关代谢产物;
多组学方法也可鉴定编码代谢物前体的基因;
如后续机制研究确立因果关系,特定菌株就可成诊断生物标志物和治疗靶标。
延伸阅读
Genome Medicine [IF:8.898]

Strain-level dissection of the contribution of the gut microbiome to human metabolic disease

针对肠道微生物组对人体代谢疾病的贡献,作菌株水平的分析

2016-04-20, Opinion, 10.1186/s13073-016-0304-1more

Abstract:
The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recent advances in genomic and metabolomic technologies are facilitating strain-level dissection of the contribution of the gut microbiome to metabolic diseases. Interventional studies and correlation analysis between variations in the microbiome and metabolome, captured by longitudinal sampling, can lead to the identification of specific bacterial strains that may contribute to human metabolic diseases via the production of bioactive metabolites. For example, high-quality draft genomes of prevalent gut bacterial strains can be assembled directly from metagenomic datasets using a canopy-based algorithm. Specific metabolites associated with a disease phenotype can be identified by nuclear magnetic resonance-based metabolomics of urine and other samples. Such multi-omics approaches can be employed to identify specific gut bacterial genomes that are not only correlated with detected metabolites but also encode the genes required for producing the precursors of those metabolites in the gut. Here, we argue that if a causative role can be demonstrated in follow-up mechanistic studies--for example, using gnotobiotic models--such functional strains have the potential to become biomarkers for diagnostics and targets for therapeutics.

First Authors:
Chenhong Zhang

Correspondence Authors:
Liping Zhao

All Authors:
Chenhong Zhang,Liping Zhao