Immunobiology and Infection Subgroup mini-symposium

Wednesday, June 16 at 09:30am (PDT)
Wednesday, June 16 at 05:30pm (BST)
Thursday, June 17 01:30am (KST)

SMB2021 SMB2021 Follow Wednesday (Thursday) during the "MS13" time block.
Note: this minisymposia has multiple sessions. The second session is MS14-IMMU (click here).

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Stanca Ciupe (Virginia Tech, United States), Jessica Conway (Penn State University, USA), Amber Smith (University of Tennessee Health Science Center, USA), Jonathan Forde (Hobart and William Smith Colleges, USA)


The Immunobiology and Infection Subgroup was created to bring together researchers in the SMB community who are interested in the modeling and analysis of immune processes in human disease and of host-pathogen interactions. Our broad objective is to discuss various topics including - within-host infectious diseases - host immune responses - causes and effects of inflammation - disease progression and outcome - integration of experimental and clinical data into models - model-driven experimental design In our 2021 mini-symposium, we will focus on infection and host immune responses to both infectious and non-infectious insults. We will have speakers with expertise in these areas. The talks will also showcase diverse modeling styles and integration with data.

James Faeder

(University of Pittsburg, USA)
"Multiscale Modeling of Viral Replication and Interferon-mediated Immune Responses"
Most intrahost models of viral infections track virus are built on ordinary differential equations that track viral and cell population but that simplify processes at the intracellular level. While these models have yielded key insights into the factors that affect viral load kinetics and have identified how factor such as timing and mechanism can determine treatment efficacy, there are several questions that require more detailed modeling of interactions at the molecular level. In particular, viral replication products and host signaling pathways interact in numerous ways that determine both the quantitative and qualitative outcomes of infection. For example, type I interferon (IFN) responses elicited by virus infection of cells in lymphoid tissues near the sites of infection not only mediate resistance of the infected cells to viral replication, but also may provide systemic resistance. In particular, with encephalitic alphaviruses, the antiviral state is stimulated in the brain early after peripheral infection. It is important to understand the characteristics and cell types involved in this early interferon stimulation as they may be protective from fatal disease. We have developed an experimental model in which the encephalitic alphavirus, eastern equine encephalitis virus (EEEV), infects various types of immune cells in an in vitro culture system. Using this system we are able to measure the kinetics of various steps in viral replication and host cell response, including induction of Type I IFNs and induction of IFN-regulated genes. We will use data from this experimental model to build and calibrate a computational model that will predict cell type specific IFN responses to viral infection and the potentially distal effects of this induction on mitigating viral infections. We will used this integrated experimental and model-based approach to identify key control mechanisms in viral and host dynamics that could be utilized for design of therapies to mitigate the effects of viral infection.

Hana Dobrovolny

(Texas Christian University, USA)
"An ODE model of syncytia formation during viral infections"
Several viral infections are known to form syncytia, which are multinuclear cells created by cells that have fused together. Little is known, however, about how the syncytia alter viral dynamics. We use an ODE model to study how different assumptions about the viral production of syncytia and lifespan of syncytia change the resulting infection time course. We find that the effect of syncytia on viral titer is only apparent when the basic reproduction number for infection via syncytia formation is similar to the reproduction number for cell free viral transmission. When syncytia fusion rate is high, we find the presence of syncytia can lead to long-lasting infections if viral production is suppressed in syncytia.

Daniel Reeves

(Fred Hutchinson Cancer Research Center, USA)
"Merging viral dynamics and phylogenetics reveals host-mediated selection may be sufficient, but not necessary, to explain within-host HIV evolution"
Modern HIV research depends crucially on both viral sequencing and population size measurements. To directly link mechanistic biological processes and evolutionary dynamics during HIV infection, we developed multiple within-host phylodynamic (wi-phy) models of HIV primary infection for comparative validation against viral load and evolutionary dynamics data. The most parsimonious and accurate model required no explicit immune selection, suggesting that the host adaptive immune system reduces viral load, but does not drive observed viral evolution. Rather, genetic drift primarily dictates fitness changes. These results hold during early infection. Moreover, during chronic infection — a setting in which adaptive immune selection has been observed -- viral fitness distributions are not largely different from in vitro distributions that emerge without adaptive immunity. Simulations highlight how phylogenetic inference must consider complex viral and immune-cell population dynamics to gain accurate mechanistic insights.

Jessica Conway

(Penn State University, USA)
"Unified model of short- and long-term HIV viral rebound"
Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. Typically suspension of therapy is rapidly followed by rebound of viral loads to high, pre-therapy levels. Indeed, a recent study showed that approximately 90% of treatment interruption study participants show viral rebound within at most a few months of therapy suspension, but the remaining 10%, showed viral rebound some months, years, or maybe permanently, after ART suspension. Design of therapeutic interventions to expand this latter group are underway. However, an understanding of the heterogeneity in rebound dynamics, crucial in design of clinical trials to test these interventions, is lacking. We will discuss our branching process model to gain insight into these post-treatment dynamics. Specifically we provide theory that explains both short- and long-term viral rebounds, and post-treatment control, via a branching process model with time-inhomgeneous rates, validated with data from Li et al. (2016). We will discuss the associated biological interpretation and implications. Finally we will provide an example of how our modeling can be used to inform HIV treatment suspension study design.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.