A clinically parameterized mathematical model of Shigella immunity to inform vaccine design
MetadataShow full item record
AbstractWe refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella0s lipopolysaccharide (LPS) and O-membrane proteins (OMP) were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella0s LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1) the rate that Shigella migrates into the lamina propria or epithelium, 2) the rate that memory B cells (BM) differentiate into antibody-secreting cells (ASC), 3) the rate at which antibodies are produced by activated ASC, and 4) the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine.
DescriptionAll relevant data are available from the Dryad Digital Repository at the following DOI: 10.5061/dryad.sq4f7.
CitationDavis CL, Wahid R, Toapanta FR, Simon JK, Sztein MB. (2018). A clinically parameterized mathematical model of Shigella immunity to inform vaccine design. PLoS ONE, 13(1), e0189571, DOI: https://doi.org/10.1371/journal.pone.0189571
SponsorsThis work was supported in part by U19 AI082655 (Cooperative Center for Human Immunology; CCHI, to MBS) from the Division of Allergy, Immunology and Transplantation (DAIT), National Institutes of Health, DHHS. It was also supported in part by a University of Maryland, College Park and University of Maryland, Baltimore (UMCP-UMB) Seed Grant (to JKS and RW).
Identifier to cite or link to this itemhttp://hdl.handle.net/10713/7582
The following license files are associated with this item:
- Creative Commons