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Original Research ARTICLE

Front. Immunol. | doi: 10.3389/fimmu.2021.639491

VaximmutorDB: A web-based vaccine immune factor database and its data analysis for understanding vaccine-induced immune responses Provisionally accepted The final, formatted version of the article will be published soon. Notify me

 Kimberly Berke1,  Peter Sun1,  Edison Ong2,  Nasim Sanati3,  Anthony Huffman2, Timothy Brunson3, Fred Loney3, Joseph Ostrow1, Rebecca Racz1, Bin Zhao4, Zuoshuang Xiang5,  Anna Maria Masci6, Jie Zheng7,  Guanming Wu3* and  Yongqun Oliver He2, 8*
  • 1College of Literature, Science, and the Arts, University of Michigan, United States
  • 2Department of Computational Medicine and Bioinformatics, School of Medicine, University of Michigan, United States
  • 3Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, United States
  • 4School of Information, University of Michigan, United States
  • 5Unit for Laboratory Animal Medicine, University of Michigan Medical School, United States
  • 6Department of Biostatistics & Bioinformatics, Duke University School of Medicine, United States
  • 7Perelman School of Medicine, University of Pennsylvania, United States
  • 8Unit for Lab Animal Medicine, Department of Microbiology & Immunology, Michigan Medicine, University of Michigan, United States

Vaccines stimulate various immune factors critical to protective immune responses. However, a comprehensive picture of vaccine-induced immune factors and pathways have not been systematically collected and analyzed. To address this issue, we developed VaximmutorDB, a web-based database system of vaccine immune factors (abbreviated as “vaximmutors”) manually curated from peer-reviewed articles. VaximmutorDB currently stores 1,740 vaccine immune factors from 13 host species (e.g., human, mouse, and pig). These vaximmutors were induced by 154 vaccines for 46 pathogens. Top 10 vaximmutors include three antibodies (IgG, IgG2a and IgG1), Th1 immune factors (IFN-γ and IL-2), Th2 immune factors (IL-4 and IL-6), TNF-α, CASP-1, and TLR8. Many enriched host processes (e.g., stimulatory C-type lectin receptor signaling pathway, SRP-dependent cotranslational protein targeting to membrane) and cellular components (e.g., extracellular exosome, nucleoplasm) by all the vaximmutors were identified. Using influenza as a model, live attenuated and killed inactivated influenza vaccines stimulate many shared pathways such as signaling of many interleukins (including IL-1, IL-4, IL-6, IL-13, IL-20, and IL-27), interferon signaling, MARK1 activation, and neutrophil degranulation. However, they also present their unique response patterns. While live attenuated influenza vaccine FluMist induced significant signal transduction responses, killed inactivated influenza vaccine Fluarix induced significant metabolism of protein responses. Two different Yellow Fever vaccine (YF-Vax) studies resulted in overlapping gene lists; however, they shared more portions of pathways than gene lists. Interestingly, live attenuated YF-Vax simulates significant metabolism of protein responses, which was similar to the pattern induced by killed inactivated Fluarix. A user-friendly web interface was generated to access, browse and search the VaximmutorDB database information. As the first web-based database of vaccine immune factors, VaximmutorDB provides systematical collection, standardization, storage, and analysis of experimentally verified vaccine immune factors, supporting better understanding of protective vaccine immunity.

Keywords: Vaccine, vaccine immune factor, immunology, database, bioinformatics

Received: 09 Dec 2020; Accepted: 18 Feb 2021.

Copyright: © 2021 Berke, Sun, Ong, Sanati, Huffman, Brunson, Loney, Ostrow, Racz, Zhao, Xiang, Masci, Zheng, Wu and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Mx. Guanming Wu, Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, 97239-3098, Oregon, United States, wug@ohsu.edu
Prof. Yongqun Oliver He, Michigan Medicine, University of Michigan, Unit for Lab Animal Medicine, Department of Microbiology & Immunology, Ann Arbor, 48109, MI, United States, yongqunh@med.umich.edu