Subgroup Contributed Talks

eSMB2020 eSMB2020 Follow Thursday at 1:30pm EDT
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Sahak Makaryan

University of Southern California
"In Silico Control and Optimization of Granzyme B and Perforin-1 Secretion in Natural Killer Cells"
Natural killer (NK) cells are immune effector cells that can detect and lyse cancer cells. NK cell exhaustion, a phenotype characterized by reduced effector functionality, can limit the NK cell’s capacity for cell lysis. The processes mediating NK cell exhaustion are many, unfortunately, rendering a single preventative approach unlikely to be optimal in all cases. In lieu of prevention, we investigated in silico whether the effects of exhaustion can be nullified by strategies that maximize the continuous secretion of effector molecules. Here, we constructed a system of nonlinear ordinary differential equations (ODEs) that describes the dynamics of the cytolytic molecules granzyme B (GZMB) and perforin-1 (PRF1). The model predictions were calibrated to published, experimental data where the model parameters were estimated via the Metropolis-Hastings algorithm. Furthermore, the model was interrogated using an information-theoretic global sensitivity analysis, to determine which model parameters (i.e., inputs) shared a significant degree of mutual information with the secreted amount of effector molecules (i.e., outputs). Interestingly, we found the inhibition of phosphatase activity maximizes the secretion of GZMB and PRF1. We appended the baseline model with a system of ODEs describing a synthetic Notch (synNotch) signaling circuit as a method for controlling the production and secretion of the cytolytic molecules. Briefly, the synNotch receptor is chimeric molecule consisting of a target-ligand specific single-chain variable fragment (scFv) in its extracellular domain, a string of cleavable amino acid sequences in its transmembrane domain and a transcription factor in its intracellular domain. Once bound to a target ligand, the synNotch receptor is cleaved by membrane proteases. This unchains the transcription factor from the cell membrane, and thereby freeing the molecule to initiate gene expression by binding to a plasmid. We included two separate plasmids in the model: (1) a multi-cistronic plasmid coding for the effector molecules and (2) a plasmid coding for a long-noncoding RNA (lncRNA) molecule that binds and sequesters the phosphatase from inhibiting signal transduction. The synNotch model was optimized by determining the optimal quantity of plasmids and synNotch receptor to maximize the secretion of the effector molecules while using the minimum amount of material. We found the optimal synNotch system depends on the frequency of NK cell stimulation: for fewer rounds of stimulation, both plasmids should be given at maximal dose; for many rounds of stimulation, the model predicts only the cytolytic molecule-coding plasmid should be given and at maximal value. This suggests that inhibition of phosphatase activity, while beneficial in the short-term, is not optimal for multiple rounds of stimulation. In total, we developed a theoretical framework that provides actionable insight into engineering robust NK cells for clinical applications.

Naveen Vaidya

San Diego State University
"HIV Infection and Antiretroviral Therapy: the Brain as a Reservoir"
It is not fully understood whether the brain acts as an HIV reservoir causing obstacle to cure through treatment. In this talk, I will present a novel mathematical model describing virus dynamics under antiretroviral therapy to study the role of the brain in virus persistence. Using experimental data from SIV infected macaques, we identify key parameters related to the brain infection, including virus-transfer across blood-brain barrier. Our model predicts that the brain can be an important reservoir causing long-term virus persistence in the brain, despite successful control of viral load in the plasma by antiretroviral drugs.

Cristina Leon

RUDN University, Russia
"Reaction-diffusion model of viruses coexistence in the space of genotypes"
We propose a mathematical model describing the competition of two viruses, in the host organism, taking into account virus mutation, reproduction, and genotype dependent mortality, either natural or determined by an antiviral treatment. The model describes the virus density distribution u(x; t) for the first virus and v(y; t) for the second one as functions of genotypes x and y considered as continuous variables and of time t. The model consists of a system of reaction-diffusion equations with integral terms characterizing virus competition for host cells. The analysis of the model shows the conditions of virus coexistence or elimination in the host organism. This study continues the cycle of works devoted to reaction-diffusion models of virus mutation and evolution.

Mohammad Aminul Islam

Oklahoma State University
"Computational modeling of the gut-bone axis and implications of butyrate treatment on osteoimmunology"
The interplay between gut microbiota and the immune system has a pivotal role in the maintenance of bone health. Recently, short-chain fatty acids (SCFAs) produced by gut microbiota have emerged as key regulatory participants in shaping the immune system. Butyrate, the most versatile among SCFAs, has been observed to have local and systemic effects including inducing the differentiation of peripheral regulatory T cells (Tregs) in the intestine, blood, and bone marrow [1]. Tregs are the central actors of the negative feedback component of the immune system. The interaction between Tregs and cytotoxic CD8+ T cells suppress the inflammatory status and promote the production of Wnt10b to increase bone anabolism [2]. Studies in the mouse models show that the ablation of butyrate in the intestine alters the bone marrow density. However, the therapeutic benefit of butyrate in bone anabolism remains poorly understood. We developed a multi-compartment physiologically based pharmacokinetic model to track and quantify the effects of butyrate on Tregs in the gut, blood, and bone marrow. The model consists of five species butyrate, naive CD4+ T cells, Tregs, TGF-β, and Wnt10b distributed across three compartments intestine, blood, and bone. We consider an open system with the processes of formation, excretion, differentiation, cell death, and migration to another compartment. The variation of butyrate concentration from homeostasis value changes the percentage of Tregs, and the production of TGF-β, and Wnt10b. Using the model, we analyze experimental data reported in [2] to evaluate the expansion of Tregs, TGF-β, and Wnt10b in the bone marrow. The probiotic LGG increases butyrate concentration in the intestine and serum blood by 0.18 μM and 0.29 μM respectively. Our simulation result shows 5% increase of Tregs, 3.4-fold increase of TGF-β, and 3-fold increase of Wnt10b in the bone marrow consistent with the net change information due to stimulus of a probiotic microbiota in the gut. The computational approach described here gives insight into the pharmacokinetics of butyrate, biodistribution of Tregs in the gut-bone axis, fold changes of Wnt10b in bone marrow, and their contributions to modulating bone formation. Research reported in this abstract was supported by NIH NIGMS R35GM133763.

Georges Ferdinand Randriafanomezantsoa Radohery

Kirby Institute, University of New South Wales, Sydney
"Incorporating parasite viability data into PK/PD modelling of artemisinin treatment of human malaria"
Malaria is a global health threat killing one child every two minutes. The rise of artemisinin resistance, which is the main component of most recommended anti-malarial regimens, has prompted the need to develop better alternative antimalarial treatments. Modelling plays an important role in the development of these new antimalarial drugs. Pharmacokinetic/Pharmacodynamic (PK/PD) models of antimalarial treatment, which relate drug concentration to parasite killing, are central in assessing and optimizing drug therapy effectiveness. A common assumption in these models is that the parasites that remain in circulation after treatment are all viable. Recently a method was developed to estimate the concentration of viable parasites after artesunate treatment, rather than simply total parasite numbers. Here, we aimed to include this additional parasite viability information into an adapted PK/PD model to more accurately estimate the drug killing rate in sensitive and resistant infections. We use data from volunteers infected with artemisinin-sensitive or resistant P. falciparum blood-stage parasites and treated with a single dose of oral artesunate monotherapy during a volunteer infection study. Parasite qPCR counts before and after treatment, the proportion of viable parasites after treatment and dihydroartemisinin plasma concentration were obtained and modelled using age-structured P. falciparum parasite population growth and a PK/PD model. We use these models for separately measuring parasite killing rate and parasite clearance rate. The addition of viability data into PK/PD model of artesunate monotherapy provided a good fit of the data. The model estimated an in vivo DHA’s EC50 of 1.42 μg/L (95% CI: 0.07, 2.78). In artemisinin-sensitive infections, the parasites mean killing half-life is 0.20 h (95% CI: 0.16 h,0.26 h) and the mean removal half-life of dead parasites was 2.77 h (95% CI: 2.4 h, 3.4 h). Further, we showed that the reduced killing observed in resistant infections were consistent with a 9-fold reduction in the sensitivity of parasites in the first 12 h of the lifecycle, and drug-killed resistant parasites were estimated to be removed slower than drug-killed sensitive parasites. Incorporating parasite viability data into PK/PD models allows refining the estimation of parasite killing rates and provides information on the stage-specific activity of antimalarial drugs in vivo. Killing half-life is faster than previously thought. These differences are likely to have important implications for optimal dosing strategies and predicting overall drug efficacy.

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Virtual conference of the Society for Mathematical Biology, 2020.