Ottawa Institute of Systems Biology and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa , Ottawa, Ontario, Canada , K1H 8M5.
Department of Chemistry, Southern University of Science and Technology , Shenzhen 518055, Guangdong, China.
Anal Chem. 2017 Sep 5;89(17):9407-9415. doi: 10.1021/acs.analchem.7b02224. Epub 2017 Aug 11.
Host-microbiome interactions have been shown to play important roles in human health and diseases. Most of the current studies of the microbiome have been performed by genomic approaches through next-generation sequencing. Technologies, such as metaproteomics, for functional analysis of the microbiome are needed to better understand the intricate host-microbiome interactions. However, significant efforts to improve the depth and resolution of gut metaproteomics are still required. In this study, we combined an efficient sample preparation technique, high resolution mass spectrometry, and metaproteomic bioinformatics tools to perform ultradeep metaproteomic analysis of human gut microbiome from stool. We reported the deepest analysis of the microbiome to date with an average of 20 558 protein groups identified per sample analysis. Moreover, strain resolution taxonomic and pathway analysis using deep metaproteomics revealed strain level variations, in particular for Faecalibacterium prausnitzii, in the microbiome from the different individuals. We also reported that the human proteins identified in stool samples are functionally enriched in extracellular region pathways and in particular those proteins involved in defense response against microbial organisms. Deep metaproteomics is a promising approach to perform in-depth microbiome analysis and simultaneously reveals both human and microbial changes that are not readily apparent using the standard genomic approaches.
宿主-微生物组相互作用已被证明在人类健康和疾病中起着重要作用。大多数目前的微生物组研究都是通过基因组方法，即下一代测序来进行的。需要用于微生物组功能分析的技术，如代谢蛋白质组学，以更好地理解复杂的宿主-微生物组相互作用。然而，仍需要做出重大努力来提高肠道代谢蛋白质组学的深度和分辨率。在这项研究中，我们结合了一种高效的样品制备技术、高分辨率质谱和代谢蛋白质组学生物信息学工具，对粪便中的人类肠道微生物组进行了超深度代谢蛋白质组学分析。我们报告了迄今为止最深入的微生物组分析，每个样本分析平均可鉴定出 20,558 个蛋白质组。此外，使用深度代谢蛋白质组学进行的分类和途径分析表明，不同个体的微生物组中存在菌株水平的变化，特别是粪拟杆菌（Faecalibacterium prausnitzii）。我们还报告说，在粪便样本中鉴定出的人类蛋白质在细胞外区域途径中具有功能富集，特别是那些涉及防御微生物的蛋白质。深度代谢蛋白质组学是一种很有前途的方法，可以进行深入的微生物组分析，同时揭示使用标准基因组方法不易察觉的人类和微生物变化。
