In-silico analysis of the 'memory anti-Naïve' effect in anti-viral cross-reactive responses

Filippo Castiglione, Dario Ghersi, Franco Celada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Of the examples of clonal competition for antigen among lymphocytes, the recently predicted 'Memory anti-Naïve' phenomenon occurs when the challenging antigen is not identical to the priming, and will be consequently bound with lower avidity by preexisting memory cells. In this study we use computer modeling and a systematic schedule of viral injections to disentangle the complex relationship between different lineages of effector T cells in the presence of viruses. We measure the antiviral efficiency of memory cells as well as their dominance over naïve cells as a function of the antigenic distance between first and second infection. Our simulation show that at a critical range of antigenic distance memory cells, now unable to clear the infection, can however block the surge of naïve clones thus preventing an effective immune response. This finding motivate us to propose the Memory anti-Naïve phenomenon as the causative mechanism for the classic Original Antigenic Sin phenomenon described in the literature which occurs irregularly in returning pandemics, and also for the less glamorous, but certainly numerous and severe, cases of misfired vaccinations, and viral escapes.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1433-1437
Number of pages5
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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    Castiglione, F., Ghersi, D., & Celada, F. (2017). In-silico analysis of the 'memory anti-Naïve' effect in anti-viral cross-reactive responses. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 1433-1437). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217873