Browsing publications of the working group of computational biology for individualized medicine ([CiiM] BIIM) by Subjects
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BCG-induced protection against Mycobacterium tuberculosis infection: Evidence, mechanisms, and implications for next-generation vaccines.The tuberculosis (TB) vaccine Bacillus Calmette-Guérin (BCG) was introduced 100 years ago, but as it provides insufficient protection against TB disease, especially in adults, new vaccines are being developed and evaluated. The discovery that BCG protects humans from becoming infected with Mycobacterium tuberculosis (Mtb) and not just from progressing to TB disease provides justification for considering Mtb infection as an endpoint in vaccine trials. Such trials would require fewer participants than those with disease as an endpoint. In this review, we first define Mtb infection and disease phenotypes that can be used for mechanistic studies and/or endpoints for vaccine trials. Secondly, we review the evidence for BCG-induced protection against Mtb infection from observational and BCG re-vaccination studies, and discuss limitations and variation of this protection. Thirdly, we review possible underlying mechanisms for BCG efficacy against Mtb infection, including alternative T cell responses, antibody-mediated protection, and innate immune mechanisms, with a specific focus on BCG-induced trained immunity, which involves epigenetic and metabolic reprogramming of innate immune cells. Finally, we discuss the implications for further studies of BCG efficacy against Mtb infection, including for mechanistic research, and their relevance to the design and evaluation of new TB vaccines.
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.