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Updated: Sep 22, 2025
Use of an Influenza Antigen Microarray to Measure the Breadth of Serum Antibodies Across Virus Subtypes
Published on: July 26, 2019
Application of a Neisseria meningitidis antigen microarray to identify candidate vaccine proteins from a human Phase
Chun-Mien Chang1, Amaka M Awanye1, Leanne Marsay2
1Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PL, UK.
Abstract:
Meningococcal meningitis is a rare but serious condition affecting mainly children and young adults. Outer membrane vesicles (OMV) from Neisseria meningitidis have been used successfully as vaccines against the disease, although they only provide protection against a limited number of the many existing variants. There have been many attempts to identify suitable protein antigens for use in defined vaccines that provide broad protection against the disease, such as that leading to the development of the four component 4CMenB vaccine. We previously reported the use of a protein antigen microarray to screen for IgG antibodies in sera derived from human recipients of an OMV-based vaccine, as part of a Phase I clinical trial. Here, we show that computational methods can be used to cluster antigens that elicit similar responses in the same individuals. Fitting of IgG antibody binding data to 4,005 linear regressions identified pairs of antigens that exhibited significant correlations. Some were from the same antigens in different quaternary states, whilst others might be correlated for functional or immunological reasons. We also conducted statistical analyses to examine correlations between individual serum bactericidal antibody (SBA) titres and IgG reactivity against specific antigens. Both Kendall's tau and Spearman's rank correlation coefficient statistics identified specific antigens that correlated with log(SBA) titre in five different isolates. The principal antigens identified were PorA and PorB, RmpM, OpcA, and the type IV pilus assembly secretin, PilQ. Other minor antigens identified included a lipoprotein, two proteins from the BAM complex and the efflux channel MtrE. Our results suggest that consideration of the entire antigen composition, and allowance for potential interaction between antigens, could be valuable in designing future meningococcal vaccines. Such an approach has the advantages that it uses data derived from human, rather than animal, immunization and that it avoids the need to screen individual antigens.
Insights
Computational analysis of immune responses to meningococcal vaccines identified correlated antigens. This approach aids in designing broader protection vaccines by considering antigen interactions and human immune data.
Area of Science:
- Immunology
- Vaccinology
- Computational Biology
Background:
- Meningococcal meningitis poses a significant threat, particularly to children and young adults.
- Current outer membrane vesicle (OMV) vaccines offer limited protection against diverse Neisseria meningitidis strains.
- Developing defined vaccines with broad protection, like the 4CMenB vaccine, is crucial.
Purpose of the Study:
- To investigate computational methods for clustering antigens based on immune responses.
- To identify correlations between antibody levels and serum bactericidal activity (SBA) against Neisseria meningitidis.
- To inform the design of future meningococcal vaccines with enhanced protective capabilities.
Main Methods:
- Utilized a protein antigen microarray to screen IgG antibodies from human vaccine recipients.
- Applied computational methods to cluster antigens eliciting similar antibody responses.
- Performed statistical analyses (Kendall's tau, Spearman's rank) to correlate IgG reactivity with SBA titres.
Main Results:
- Identified significant correlations between pairs of antigens, suggesting functional or immunological links.
- Specific antigens, including PorA, PorB, RmpM, OpcA, and PilQ, correlated with SBA titres against multiple meningococcal isolates.
- Discovered minor antigen correlations, such as with a lipoprotein, BAM complex proteins, and MtrE.
Conclusions:
- Computational clustering of antigen-specific immune responses provides insights into vaccine efficacy.
- Considering antigen composition and interactions is valuable for designing next-generation meningococcal vaccines.
- This human data-driven approach avoids animal immunization and individual antigen screening.
