Browsing publications of the working group of computational biology for individualized medicine ([CiiM] BIIM) by Subjects
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Resolving trained immunity with systems biology.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 re-stimulation, and is mediated through epigenetic and metabolic modifications. In this review, we describe how molecular mechanisms underlying trained immunity, for example induced by β-glucan or Bacille Calmette-Guérin (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 inter-individual 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. This article is protected by copyright. All rights reserved.