Boosting and modeling immunity: integrated approaches in tuberculosis vaccine development

Abstract

Tuberculosis (TB) disease caused by Mycobacterium tuberculosis (Mtb) has returned as the leading cause of death by an infectious agent in 2023, and approximately 25% of the global population is infected with Mtb. There is only one licensed vaccine, Bacillus Calmette–Guérin (BCG), a live attenuated strain of Mycobacterium bovis. While the World Health Organization estimates that global BCG vaccination coverage was 87% as of 2023, TB remains a top 10 cause of mortality overall, claiming a life every 30s. It is without doubt that BCG alone is not enough to protect against TB and any newly developed vaccines must complement the baseline protection already offered by BCG. To address these gaps, we established two complementary approaches. This dissertation outlines the development of a vaccine booster to BCG using a novel inactivated Mtb (SolaVAX-Mtb) and the establishment of a Generalized Linear Model (GLM) statistical framework to evaluate high-dimensional flow cytometry data and the multivariable influences on immune responses using a clinical trial booster. We find that BCG prime and boost with SolaVAX-Mtb significantly reduces lung colony forming units and lesion burden, while increasing correlates of mucosal immunity. In our GLM analysis, mice showed increased probabilities of T cell activation in the lung following BCG + ID93-GLA-SE compared to BCG or ID93-GLA-SE alone, with females showing more robust B cell responses. This dissertation underscores the importance of multivariable influences in TB immunology and the benefits of boosting mucosal immunity to improve baseline BCG protection—ultimately paving the way for more effective TB prevention strategies.