Chapter Three: System-level integrative omics analysis to identify the virus-host immunometabolic footprint during infection.

Autor: Ambikan, Anoop, Akusjärvi, Sara Svensson, Sperk, Maike, Neogi, Ujjwal
Předmět:
Zdroj: Advances in Immunology; 2024, Vol. 164, p73-100, 28p
Abstrakt: The emergence and re-emergence of infectious diseases present significant global health threats. Understanding their pathogenesis is crucial for developing diagnostics, therapeutics, and preventive strategies. System-level integrative omics analysis offers a comprehensive approach to deciphering virus-host immunometabolic interactions during infections. Multi-omics approaches, integrating genomics, transcriptomics, proteomics, and metabolomics, provide holistic insights into disease mechanisms, host-pathogen interactions, and immune responses. The interplay between the immune system and metabolic processes, termed immunometabolism, has gained attention, particularly in infectious diseases. Immunometabolic studies reveal how metabolic processes regulate immune cell function, shaping immune responses and influencing infection outcomes. Metabolic reprogramming is crucial for immune cell activation, differentiation, and function. Using systems biological algorithms to understand the immunometabolic alterations can provide a holistic view of immune and metabolic pathway interactions, identifying regulatory nodes and predicting responses to perturbations. Understanding these pathways enhances the knowledge of immune regulation and offers avenues for therapeutic interventions. This review highlights the contributions of multi-omics systems biology studies in understanding infectious disease pathogenesis, focusing on RNA viruses. The integrative approach enables personalized medicine strategies, considering individual metabolic and immune variations. Leveraging these interdisciplinary approaches promises advancements in combating RNA virus infections and improving health outcomes, highlighting the transformative impact of multi-omics technologies in infectious disease research. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index
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