Centre for Microbial Diseases and Immunity Research, University of British Columbia, Vancouver, BC, Canada.
Molecular Biology & Biochemistry Department, Simon Fraser University, Burnaby, BC, Canada.
Front Immunol. 2020 Jul 30;11:1683. doi: 10.3389/fimmu.2020.01683. eCollection 2020.
Systems biology is an approach to interrogate complex biological systems through large-scale quantification of numerous biomolecules. The immune system involves >1,500 genes/proteins in many interconnected pathways and processes, and a systems-level approach is critical in broadening our understanding of the immune response to vaccination. Changes in molecular pathways can be detected using high-throughput omics datasets (e.g., transcriptomics, proteomics, and metabolomics) by using methods such as pathway enrichment, network analysis, machine learning, etc. Importantly, integration of multiple datasets is becoming key to revealing novel biological insights. In this perspective article, we highlight the use of protein-protein interaction (PPI) networks as a multi-omics integration approach to unravel information flow and mechanisms during complex biological events, with a focus on the immune system. This involves a combination of tools, including: , a database of curated interactions between genes and protein products involved in the innate immunity; , a visualization and analysis platform for InnateDB interactions; and , a tool to integrate metabolite data into PPI networks. The application of these systems techniques is demonstrated for a variety of biological questions, including: the developmental trajectory of neonates during the first week of life, mechanisms in host-pathogen interaction, disease prognosis, biomarker discovery, and drug discovery and repurposing. Overall, systems biology analyses of omics data have been applied to a variety of immunology-related questions, and here we demonstrate the numerous ways in which PPI network analysis can be a powerful tool in contributing to our understanding of the immune system and the study of vaccines.
系统生物学是一种通过大规模量化大量生物分子来研究复杂生物系统的方法。免疫系统涉及 >1500 个基因/蛋白质,存在于许多相互关联的途径和过程中,系统级的方法对于拓宽我们对疫苗接种免疫反应的理解至关重要。可以使用高通量组学数据集(例如转录组学、蛋白质组学和代谢组学),通过途径富集、网络分析、机器学习等方法来检测分子途径的变化。重要的是,整合多个数据集正成为揭示新生物学见解的关键。在这篇观点文章中,我们强调了使用蛋白质-蛋白质相互作用(PPI)网络作为一种多组学整合方法,以揭示复杂生物学事件中的信息流和机制,重点关注免疫系统。这涉及到一系列工具的组合,包括: ,一个包含先天免疫中涉及的基因和蛋白质产物之间已验证相互作用的数据库; ,一个用于 InnateDB 相互作用的可视化和分析平台; ,一个将代谢物数据整合到 PPI 网络中的工具。这些系统技术的应用已针对各种生物学问题进行了演示,包括:新生儿在生命的第一周内的发育轨迹、宿主-病原体相互作用中的机制、疾病预后、生物标志物发现以及药物发现和再利用。总体而言,组学数据分析已应用于各种与免疫学相关的问题,在这里我们展示了 PPI 网络分析可以成为理解免疫系统和研究疫苗的有力工具的多种方式。