Computational Modeling of Immune Responses to Clostridium difficile Infection for Predicting Therapeutic Efficacy
Abstract
The long-term goal of this proposal is to develop computational and mathematical models of the immune response to toxicogenic bacteria, which can be deployed to accelerate research on measures for counter Weapons of Mass Destruction (cWMD) by recalibration with pathogen-specific data. We will use Clostridium difficile infection (CDI) as a proof-of-concept organism to assess its impact on kinetics of host responses because of the limited availability of clinical data for select agents and the existence of experimental mouse models of CDI that can be used for validation purposes. In addition, the incidence of community and health-associated C. difficile has increased in the U.S. military population. We will design multiscale computational models of host responses to the pathogen that enable a systems-wide analysis and accelerated identification of host factors critical to overcome the infection. These factors could potentially be used for therapeutic development and as precision medicine biomarkers. The models will represent interactions between the bacteria and released toxins (tcdA and tcdB) on the pathogen side, and cellular and humoral immune responses (T cell differentiation, B cell responses, anti-toxin-specific immunoglobulins, and antimicrobial peptide production) on the host side. At the molecular level, we will represent the metabolic adaptation of CD4+ T cells and B cells, and their influence on effector responses targeting the bacteria and toxins. We will employ models that combine advanced machine-learning (ML) algorithms, ordinary differential equation (ODE) and agent-based modeling (ABM), and apply sensitivity analysis to rank factors determining clinical and pathological outcomes and predict where small changes to assumptions may result in large changes to end-state predictions of the host-C. difficile interaction. The computational models developed by MIDK-cWMD will represent the linkages between the host response and metabolism implicated in targeting the bacteria and their toxins. Once the CDI model is optimized, we will use it to model infection with Bacillus anthracis, including the kinetics of toxin release, their role in disarming the innate immune response and the molecular mechanisms of action of lethal and edema toxins at the cellular level.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 16, 2019
- Source ID
- HDTRA11810008
Entities
People
- Josep Bassaganyariera
Organizations
- Defense Threat Reduction Agency
- Virginia Tech