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Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

期刊

FRONTIERS IN IMMUNOLOGY
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2021.574411

关键词

artificial intelligence; dengue; antibody discovery; B-cell receptor; immune repertoire; virus; immunotherapy; machine learning

资金

  1. Wellcome Trust [215840/Z/19/Z]
  2. Wellcome Trust [215840/Z/19/Z] Funding Source: Wellcome Trust

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The Dengue virus poses a serious threat as the causative agent of Dengue fever, with millions of infection cases each year in over 128 countries. Despite the lack of approved treatment or fully efficacious vaccine, researchers are utilizing high-throughput sequencing and computational analysis tools to understand the complexities of DENV immune response.
Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1-5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.

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