De novo identification of bacterial antigens of a clinical isolate by combining use of proteosurfaceomics, secretomics, and BacScan technologies

Front Immunol. 2023 Nov 30:14:1274027. doi: 10.3389/fimmu.2023.1274027. eCollection 2023.

Abstract

Background: Emerging infectious diseases pose a significant threat to both human and animal populations. Rapid de novo identification of protective antigens from a clinical isolate and development of an antigen-matched vaccine is a golden strategy to prevent the spread of emerging novel pathogens.

Methods: Here, we focused on Actinobacillus pleuropneumoniae, which poses a serious threat to the pig industry, and developed a general workflow by integrating proteosurfaceomics, secretomics, and BacScan technologies for the rapid de novo identification of bacterial protective proteins from a clinical isolate.

Results: As a proof of concept, we identified 3 novel protective proteins of A. pleuropneumoniae. Using the protective protein HBS1_14 and toxin proteins, we have developed a promising multivalent subunit vaccine against A. pleuropneumoniae.

Discussion: We believe that our strategy can be applied to any bacterial pathogen and has the potential to significantly accelerate the development of antigen-matched vaccines to prevent the spread of an emerging novel bacterial pathogen.

Keywords: A. pleuropneumoniae; de novo identification; emerging bacterial pathogens; highly immunogenic proteins; vaccine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Actinobacillus pleuropneumoniae*
  • Animals
  • Antigens, Bacterial
  • Bacterial Proteins
  • Bacterial Vaccines
  • Humans
  • Pleuropneumonia* / microbiology
  • Pleuropneumonia* / prevention & control
  • Swine

Substances

  • Antigens, Bacterial
  • Bacterial Vaccines
  • Bacterial Proteins

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The work was supported by National Key R&D Program of China (2022YFD1800903), Hubei Hongshan Laboratory (2022hszd023), Guangzhou Yingzi Technology Co., Ltd. and Huazhong Agricultural University School-Enterprise Cooperation Fund (IRIFH202209), and Natural Science Foundation of Hubei Province (2021CFA016). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.