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Applying Mathematical Tools to Accelerate Vaccine Development: Modeling Shigella Immune Dynamics

Overview of attention for article published in PLOS ONE, April 2013
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Title
Applying Mathematical Tools to Accelerate Vaccine Development: Modeling Shigella Immune Dynamics
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0059465
Pubmed ID
Authors

Courtney L. Davis, Rezwanul Wahid, Franklin R. Toapanta, Jakub K. Simon, Marcelo B. Sztein, Doron Levy

Abstract

We establish a mathematical framework for studying immune interactions with Shigella, a bacteria that kills over one million people worldwide every year. The long-term goal of this novel approach is to inform Shigella vaccine design by elucidating which immune components and bacterial targets are crucial for establishing Shigella immunity. Our delay differential equation model focuses on antibody and B cell responses directed against antigens like lipopolysaccharide in Shigella's outer membrane. We find that antibody-based vaccines targeting only surface antigens cannot elicit sufficient immunity for protection. Additional boosting prior to infection would require a four-orders-of-magnitude increase in antibodies to sufficiently prevent epithelial invasion. However, boosting anti-LPS B memory can confer protection, which suggests these cells may correlate with immunity. We see that IgA antibodies are slightly more effective per molecule than IgG, but more total IgA is required due to spatial functionality. An extension of the model reveals that targeting both LPS and epithelial entry proteins is a promising avenue to advance vaccine development. This paper underscores the importance of multifaceted immune targeting in creating an effective Shigella vaccine. It introduces mathematical models to the Shigella vaccine development effort and lays a foundation for joint theoretical/experimental/clinical approaches to Shigella vaccine design.

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The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Uruguay 1 3%
Germany 1 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 26%
Student > Ph. D. Student 6 16%
Student > Master 5 13%
Professor 2 5%
Student > Bachelor 2 5%
Other 8 21%
Unknown 5 13%
Readers by discipline Count As %
Mathematics 5 13%
Medicine and Dentistry 5 13%
Agricultural and Biological Sciences 4 11%
Immunology and Microbiology 4 11%
Biochemistry, Genetics and Molecular Biology 3 8%
Other 9 24%
Unknown 8 21%