Invited Speaker, 26th March
Prof Tim Elliott, University of Southampton, UK
Computational modelling of antigen processing and presentation
MHC-I molecules play a central role in the immune response to viruses and cancers. They present peptides on the surface of affected cells, for recognition by cytotoxic T cells. Determining which peptides are presented, and in what proportion, has profound implications for developing effective treatments. However, our ability to predict peptide presentation levels is currently limited. Existing prediction algorithms focus primarily on the binding affinity of peptides to MHC-I, and do not predict the relative abundance of individual peptides on the surface of antigen presenting cells in situ which is a critical parameter for determining the strength and specificity of the ensuing immune response. We have developed and experimentally verified a mechanistic model for predicting cell-surface presentation of competing peptides. The method explicitly models key steps in the processing of intracellular peptides, incorporating both peptide binding affinity and intracellular peptide abundance. We use the resulting model to predict how the peptide repertoire is modified by interferon-γ, an immune modulator well known to enhance expression of antigen processing and presentation proteins.
Invited Speaker, 27th March
Ralph Mueller, ETH, Zurich, Switzerland
Cell-based in silicon modeling of bone regeneration
A validated fracture healing model has the potential to reduce the need for animal testing when developing drugs and biomaterials. Current in silico models of bone regeneration lack the fidelity of physiological processes or are limited spatially making comparison to in vivo data for validation difficult. In regeneration, woven bone is produced and remodeled to the structured lamellar bone. The remodeling process is mechanically driven, thus an accurate representation of woven bone is crucial for in silico models, in which discrete mechanically sensitive cells are modeled. State-of-the-art in silico models of bone regeneration model tissue as a continuum. As part of the lecture, a novel fracture healing model on the microstructural level will be presented. The focus will be on investigating the effect of initial mesenchymal stem cell (MSC) density and osteoblast polarization on callus microstructure. As a geometric input for the simulations including nine cell types and tissue vascularization, in vivo micro-CT images of mice undergoing osteotomy were used. Results show polarization of osteoblasts was crucial for creating a porous microstructure. Pore size qualitatively depended on the initial population size, with fewer cells creating a finer structure in the regenerated bone.
Support from the EU (BIODESIGN FP7-NMP-2012-262948, MechAGE ERC-2016-ADG-741883) and the Swiss National Supercomputing Centre (CSCS).