Wednesday, June 16 at 06:45am (PDT)Wednesday, June 16 at 02:45pm (BST)Wednesday, June 16 10:45pm (KST)
SMB2021 FollowTuesday (Wednesday) during the "CT06" time block.
Pennsylvania State University
"Investigating model alternatives for acute HIV infection"
The standard viral dynamics model explains HIV viral dynamics during acute infection reasonably well. However, the model makes simplifying assumptions, neglecting some aspects of HIV pathogenesis. For example, in the standard model, target cells are infected by a single HIV virion. Yet, cellular multiplicity of infection (MOI) may have considerable effects in pathogenesis and viral evolution. Further when using the standard model, we take constant infected cell death rates, simplifying the dynamic immune responses. Here, we use four models—1) the standard viral dynamics model, 2) an alternate model incorporating cellular MOI, 3) a model assuming density-dependent death rate of infected cells and 4) a model combining (2) and (3)—to investigate acute infection dynamics among study participants in the RV217 dataset. We find that all models explain the data, but different models describe differing features of the dynamics more accurately. For example, while the standard viral dynamics model may be the most parsimonious model, viral peaks are better explained by a model allowing for cellular MOI. These results suggest that heterogeneity in within-host viral dynamics cannot be captured by a single model but depending on the aspect of interest, a corresponding model should be employed.
"Time to revisit the endpoint dilution assay"
A virus sample's infectivity is measured by the number of the infections it causes per unit volume, via a plaque or focus forming assay (PFU or FFU) or an endpoint dilution (ED) assay (TCID50, EID50, etc.). The plaque and focus assays have several technical and experimental limitations we will outline in this presentation, but yield a simple measure: one plaque equals one infectious dose. The ED assay does not suffer from these limitations, but as we will show, the measure it yields, the TCID50, is calculated using biased and antiquated approximations that relate poorly to the number of infectious doses in the sample. We propose taking the best of both: (1) preferring the ED assay over the more subjective plaque or focus forming assay; and (2) replacing the TCID50 with an accurate, robust and meaningful measure we call Specific INfections or SIN, corresponding to the most likely number of infections a virus sample will cause. We will demonstrate how the measure of SIN compares to current measures (FFU, TCID50) under typical experimental conditions, and how experimental protocols can be altered to yield even more accurate measures.
University of Leeds
"A stochastic intracellular model of anthrax infection with spore germination heterogeneity"
During inhalational anthrax infection, Bacillus anthracis spores are ingested by alveolar macrophages, and begin to germinate and then proliferate inside them, which may eventually lead to death of the host cell and the release of bacteria into the extracellular environment. Alternatively, some macrophages may be successful in eliminating the intracellular bacteria and will recover. In this talk, we consider a stochastic model of the intracellular infection dynamics of B. anthracis in macrophages. We explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. This model has been calibrated by means of approximate Bayesian computation, using experimental measurements. We use the calibrated stochastic model to predict the probability of rupture, mean time until rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate across different spores, with a subset of spores expected to germinate much later than the majority.
"Computational Identification of Cancer Immunotherapy Targets using Combinatorial Peptide Libraries"
The interaction between T-cell receptors (TCRs) and peptides is highly degenerate: a single TCR may recognize about one million different peptides in the context of a single MHCI molecule. On the other hand, TCR recognition is fundamentally peptide- and/or MHC-specific: the functional sensitivity, which can be viewed as experimental realisation of the TCR triggering rate, is large enough only for minute fraction of all possible ligands. TCR triggering rate and degeneracy are mathematical concepts that are fundamental for an approach that uses length-matched combinatorial peptide library (CPL) scan data to search protein databases and to rank peptides in order of likelihood recognition. This CPL-based database screening can, to a large extent, accurately identify self-peptides that triggered the CD8 T-cell. The computational time required for peptide searching can be significantly reduced by using graphics processing units (GPUs). Adoption of GPU-accelerated prediction of T-cell agonists has the capacity to revolutionise our understanding of cancer immunity by identifying potential targets for tumor-specific T-cells.