期刊
EUROPEAN JOURNAL OF IMMUNOLOGY
卷 51, 期 4, 页码 773-784出版社
WILEY
DOI: 10.1002/eji.202048882
关键词
data integration; innate immunity; multiomics; systems biology; trained immunity
类别
资金
- National Institute of Health [R01AI145781]
- ERC [833247, 948207]
- Spinoza Grant of the Netherlands Organization for Scientific Research
- Radboud University Medical Centre Hypatia Grant (2018) for Scientific Research
- European Research Council (ERC) [948207] Funding Source: European Research Council (ERC)
Trained immunity involves long-term functional reprogramming of innate immune cells, leading to enhanced responsiveness to pathogens or microbial ligands. Investigating the molecular mechanisms underlying trained immunity through various layers of information using a systems biology approach can help understand the complex interplay between molecular layers and individual variation.
Trained immunity is characterized by long-term functional reprogramming of innate immune cells following challenge with pathogens or microbial ligands during infection or vaccination. This cellular reprogramming leads to increased responsiveness upon restimulation, and is mediated through epigenetic and metabolic modifications. In this review, we describe how molecular mechanisms underlying trained immunity, for example, induced by beta-glucan or Bacille Calmette-Guerin (BCG) vaccination, can be investigated by using and integrating different layers of information including genome, epigenome, transcriptome, proteome, metabolome, microbiome, immune cell phenotyping, and function. We also describe the most commonly used experimental and computational techniques. Finally, we provide a number of examples of how a systems biology approach was applied to study trained immunity to understand interindividual variation or the complex interplay between molecular layers. In conclusion, trained immunity represents an opportunity for regulating innate immune function, and understanding the complex interplay of mechanisms that mediate trained immunity might enable us to employ it as a clinical tool in the future.
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