Peters Joshua M, Solomon Sydney L, Itoh Christopher Y, Bryson Bryan D
Department of Biological Engineering, MIT, Cambridge, MA, U.S.A.
Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, U.S.A.
Emerg Top Life Sci. 2019 Aug 16;3(4):371-378. doi: 10.1042/ETLS20180174.
Interactions between pathogens and their hosts can induce complex changes in both host and pathogen states to privilege pathogen survival or host clearance of the pathogen. To determine the consequences of specific host-pathogen interactions, a variety of techniques in microbiology, cell biology, and immunology are available to researchers. Systems biology that enables unbiased measurements of transcriptomes, proteomes, and other biomolecules has become increasingly common in the study of host-pathogen interactions. These approaches can be used to generate novel hypotheses or to characterize the effects of particular perturbations across an entire biomolecular network. With proper experimental design and complementary data analysis tools, high-throughput omics techniques can provide novel insights into the mechanisms that underlie processes from phagocytosis to pathogen immune evasion. Here, we provide an overview of the suite of biochemical approaches for high-throughput analyses of host-pathogen interactions, analytical frameworks for understanding the resulting datasets, and a vision for the future of this exciting field.
病原体与其宿主之间的相互作用可在宿主和病原体状态上引发复杂变化，以利于病原体存活或宿主清除病原体。为了确定特定宿主 - 病原体相互作用的后果，微生物学、细胞生物学和免疫学中的多种技术可供研究人员使用。能够对转录组、蛋白质组和其他生物分子进行无偏测量的系统生物学在宿主 - 病原体相互作用研究中变得越来越普遍。这些方法可用于生成新的假设或表征特定扰动对整个生物分子网络的影响。通过适当的实验设计和互补的数据分析工具，高通量组学技术可以为从吞噬作用到病原体免疫逃避等过程的潜在机制提供新的见解。在这里，我们概述了用于高通量分析宿主 - 病原体相互作用的一系列生化方法、理解所得数据集的分析框架，以及对这个令人兴奋的领域的未来展望。
