Your browser doesn't support javascript.
loading
Comparative computational modeling of the bat and human immune response to viral infection with the Comparative Biology Immune Agent Based Model
Chase Cockrell; Gary An.
Affiliation
  • Chase Cockrell; University of Vermont Larner College of Medicine
  • Gary An; University of Vermont Larner College of Medicine
Preprint in English | bioRxiv | ID: ppbiorxiv-450378
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See journal article
ABSTRACT
Given the impact of pandemics due to viruses of bat origin there is increasing interest in comparative investigation into the differences between bat and human immune responses. The practice of comparative biology can be enhanced by computational methods used for dynamic knowledge representation to visualize and interrogate the putative differences between the two systems. We present an agent-based model that encompasses and bridges the differences between bat and human responses to viral infection the Comparative Biology Immune Agent-based Model, or CBIABM. The CBIABM examines differences in innate immune mechanisms between bats and humans, specifically regarding inflammasome activity and Type 1 Interferon dynamics, in terms of tolerance to viral infection. Simulation experiments with the CBIABM demonstrate the efficacy of bat-related features in conferring viral tolerance and also suggest a crucial role for endothelial inflammasome activity as a mechanism for bat systemic viral tolerance and affecting the severity of disease in human viral infections. We hope that this initial study will inspire additional comparative modeling projects to link, compare, and contrast immunological functions shared across different species, and in so doing, provide insight and aid in the preparation for future viral pandemics of zoonotic origin.
License
cc_by_nc
Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
...