The human immune response works to either clear or control pathogens upon infection. Antigen presentation s critical to the immune response and is the process by which peptide fragments of pathogens are taken up by cells and displayed on the cell surface. Events at multiple scales (genetic molecular, cellular, tissue, and organ) are involved in antigen presentation. Briefly, antigen-presenting cells (ARC) take up pathogens at the site of infection. Once they have been taken up, they are then processed into peptides within the APC. These peptides then bind proteins known as the major histocompatibility complex (MHC). These peptide- MHC complexes (pMHC) are then displayed on the surface of the APC for recognition by T cells. In addition, the dynamics of antigen presentation and recognition are influenced by the larger tissue-level context in which they occur, namely the structured environment of the lymph node and ultimately by external compartmental dynamics of blood and the lymphatic system. A comprehensive understanding of the process of antigen presentation during an immune response will require an integrated picture of events that are occurring over multiple spatial and time scales. Mathematical models are tools that allow for such a multiscale investigation. Not surprisingly, since pathogens meet APCs continually as a first line of defense, many have evolved ways to inhibit antigen presentation. One such intracellular bacterial pathogen is Mycobacterium tuberculosis. Upon entering the lungs, M. tuberculosis is taken up by resident macrophages and then replicates. To evade immune surveillance, M. tuberculosis is known to inhibit antigen presentation of its host macrophage. The mechanisms by which M. tuberculosis achieves this inhibition have not been completely elucidated.
Our specific aims i nclude: building mathematical and statistical models to: predict affinity of peptides for different MHCII molecules with particular emphasis on the role that peptide length plays in determining affinity; describe the processing and the presentation events occurring in a single APC; describe antigen recognition and some of the downstream events by capturing interactions of cells within a single lymph node; capture relevant immune dynamics in the body in two-compartments of blood/lymph node. Integrating the models over multiple scales will be a key goal as well as utilizing data from non-human primate and mouse systems. Our specific goal is to use the models developed above towards understanding antigen presentation during M. tuberculosis infection, the causative agent of tuberculosis, and the leading cause of death due to infectious disease in the world today. As the premise behind vaccines is to train the immune system to recognize pathogens (via antigen presentation) and to quickly respond, information gained from the studies described herein can be immediately applied to vaccine design for M. tuberculosis as well as for other pathogens.
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