Interactomics: Dozens of Viruses, Co-evolving With Humans, Including the Influenza A Virus, may Actively Distort Human Aging. (17th January 2023)

• Record Type: Journal Article
• Authors: Teulière, Jérôme; Bernard, Charles; Bonnefous, Hugo; Martens, Johannes; Lopez, Philippe; Bapteste, Eric
• Editors: Leitner, Thomas
• Is Part Of: Molecular biology and evolution. Volume 40:Number 2(2023)
• Publication Date: 2023-01-17
• Subjects: protein–protein interaction -- viruses -- age-distorters -- cellular senescence -- co-evolution -- evolutionary theories of aging; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msad012
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: Some viruses (e.g., human immunodeficiency virus 1 and severe acute respiratory syndrome coronavirus 2) have been experimentally proposed to accelerate features of human aging and of cellular senescence. These observations, along with evolutionary considerations on viral fitness, raised the more general puzzling hypothesis that, beyond documented sources in human genetics, aging in our species may also depend on virally encoded interactions distorting our aging to the benefits of diverse viruses. Accordingly, we designed systematic network–based analyses of the human and viral protein interactomes, which unraveled dozens of viruses encoding proteins experimentally demonstrated to interact with proteins from pathways associated with human aging, including cellular senescence. We further corroborated our predictions that specific viruses interfere with human aging using published experimental evidence and transcriptomic data; identifying influenza A virus (subtype H1N1) as a major candidate age distorter, notably through manipulation of cellular senescence. By providing original evidence that viruses may convergently contribute to the evolution of numerous age-associated pathways through co-evolution, our network-based and bipartite network–based methodologies support an ecosystemic study of aging, also searching for genetic causes of aging outside a focal aging species. Our findings, predicting age distorters and targets for anti-aging therapies among human viruses, could have fundamental and practical implications for evolutionary biology, aging study, virology, medicine, and demography.