4.8 Article

A new framework for host-pathogen interaction research

期刊

FRONTIERS IN IMMUNOLOGY
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.1066733

关键词

host-pathogen interaction; disease outcome; COVID-19; host-coronavirus interaction; coronavirus infectious disease ontology (CIDO); bioinformatics; COVID-19 cocktail; HPIPO framework

资金

  1. NIH [UH2AI132931, U24AI171008, U24CA210967, P30ES017885, P20GM113123, 1UL1TR001412, T15LM012495]
  2. non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences [2019PT320003]
  3. University of Michigan Medical School Global Reach award
  4. COVID-19 discovery award from Michigan Medicine - Peking University Health Sciences Center Joint Institute for Clinical and Translational Research

向作者/读者索取更多资源

This paper proposes a set of postulates and a framework for understanding the complexity of host-pathogen interactions at the molecular and cellular levels in diseases like COVID-19. By establishing host-pathogen interaction postulates and an ontology framework, it enables data standardization, sharing, and analysis, providing new approaches for drug and vaccine design.
COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

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