Department of Endocrinology, Diabetes and Nutrition, Hospital of Girona 'Dr Josep Trueta', University of Girona, Girona Biomedical Research Institute (IdibGi), Spain.
CIBERobn Pathophysiology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain.
FEBS J. 2020 Mar;287(5):856-865. doi: 10.1111/febs.15130. Epub 2019 Nov 24.
Thanks to the emergence and recent advances in high-throughput sequencing technologies, it is becoming more evident every day that changes in the microbiome composition are linked to a myriad of health conditions. Despite this, the mechanisms of host-microbiota signalling remain largely unknown. The microbiome has an extensive metabolic activity that leads to the generation of a large number of compounds that are likely to influence host health. Therefore, the microbiome-host cross-talk is in part mediated by microbial-derived metabolites. Unlike metagenomics, which only provides information about microbial genes and thus the microbiome functional potential, metabolic phenotyping is well suited to capture their actual metabolic activity. Here, we provide an overview of these approaches and propose an integration of metagenomics, as a microbiome compositional readout, with faecal and plasma/urine metabolomics, as a functional readout, to unravel novel mechanisms linking the microbiome to host health and disease.
得益于高通量测序技术的出现和近期的进展,微生物组组成的变化与无数健康状况有关,这一点每天都变得更加明显。尽管如此,宿主-微生物群信号的机制在很大程度上仍然未知。微生物组具有广泛的代谢活性,会产生大量可能影响宿主健康的化合物。因此,微生物组-宿主的串扰部分是由微生物衍生的代谢物介导的。与仅提供有关微生物基因的信息,从而提供微生物组功能潜力的宏基因组学不同,代谢表型分析非常适合捕捉它们的实际代谢活性。在这里,我们概述了这些方法,并提出了将宏基因组学(作为微生物组组成的读出)与粪便和血浆/尿液代谢组学(作为功能读出)相结合,以揭示将微生物组与宿主健康和疾病联系起来的新机制的方法。