Biology subjects

Pienaar, E.

Publications and source records attributed to Pienaar, E..

7 recordsLinked to original sources

bioRxiv2023

In silico agent-based modeling approach to characterize multiple in vitro tuberculosis infection models

In vitro models of Mycobacterium tuberculosis (Mtb) infection are a valuable tool to examine host-pathogen interactions and screen drugs. With the development of more complex in vitro models, there is a need for tools to help analyze and integrate data from these models. We introduce an agent-based model (ABM) representation of the interactions between immune cells and bacteria in an in vitro setting. This in silico model was used to independently simulate both traditional and spheroid cell culture models by changing the movement rules and initial spatial layout of the cells. These two setups were calibrated to published experimental data in a paired manner, by using the same parameters in both simulations. Within the calibrated set, heterogeneous outputs are seen for outputs of interest including bacterial count and T cell infiltration into the macrophage core of the spheroid. The simulations are also able to predict many outputs with high time resolution, including spatial structure. The structure of a single spheroid can be followed across the time course of the simulation, allowing the relationship between cell localization and immune activation to be explored. Uncertainty analyses are performed for both model setups using latin hypercube sampling and partial rank correlation coefficients to allow for easier comparison, which can provide insight into ideal use cases for the independent setups. Future model iterations can be guided by the limitations of the current model, specifically which parts of the output space were harder to reach. This ABM can be used to represent more in vitro Mtb infection models due to its flexible structure, providing a powerful analysis tool that can be used in tandem with experiments. Author SummaryTuberculosis is an infectious disease that causes over 1.4 million deaths every year. During infection, immune cells surround the bacteria forming structures called granulomas in the lungs. New laboratory models generate spheroids that aim to recreate these structures to help understand infection and find new ways to treat tuberculosis. Computational modeling is used to compare these newer spheroid models to traditional models, which dont recreate the structure of the cell clusters. After calibration to data from laboratory experiments to ensure that the computational model can represent both systems, the structures were characterized over time. The traditional and spheroid model were also compared by looking at how model inputs impact outputs, allowing users to figure out when one model should be used over the other. This computational tool can be used to help integrate data from different laboratory models, generate hypothesis to be tested in laboratory models, and predict pathways to be targeted by drugs.

systems biology↗

bioRxiv2023

Mathematical modeling indicates that regulatory inhibition of CD8+ T cell cytotoxicity can limit efficacy of IL-15 immunotherapy in cases of high pre-treatment SIV viral load

Immunotherapeutic cytokines can activate immune cells against cancers and chronic infections. N-803 is an IL-15 superagonist that expands CD8+ T cells and increases their cytotoxicity. N-803 also temporarily reduced viral load in a limited subset of non-human primates infected with simian immunodeficiency virus (SIV), a model of HIV. However, viral suppression has not been observed in all SIV cohorts and may depend on pre-treatment viral load and the corresponding effects on CD8+ T cells. Starting from an existing mechanistic mathematical model of N-803 immunotherapy of SIV, we develop a model that includes activation of SIV-specific and non-SIV-specific CD8+ T cells by antigen, inflammation, and N-803. Also included is a regulatory counter-response that inhibits CD8+ T cell proliferation and function, representing the effects of immune checkpoint molecules and immunosuppressive cells. We simultaneously calibrate the model to two separate SIV cohorts. The first cohort had low viral loads prior to treatment ({approx}3-4 log viral RNA copy equivalents (CEQ)/mL), and N-803 treatment transiently suppressed viral load. The second had higher pre-treatment viral loads ({approx}5-7 log CEQ/mL) and saw no consistent virus suppression with N-803. The mathematical model can replicate the viral and CD8+ T cell dynamics of both cohorts based on different pre-treatment viral loads and different levels of regulatory inhibition of CD8+ T cells due to those viral loads (i.e. initial conditions of model). Our predictions are validated by additional data from these and other SIV cohorts. While both cohorts had high numbers of activated SIV-specific CD8+ T cells in simulations, viral suppression was precluded in the high viral load cohort due to elevated inhibition of cytotoxicity. Thus, we mathematically demonstrate how the pre-treatment viral load can influence immunotherapeutic efficacy, highlighting the in vivo conditions and combination therapies that could maximize efficacy and improve treatment outcomes. Author SummaryImmunotherapy bolsters and redirects the immune system to fight chronic infections and cancers. However, the effectiveness of some immunotherapies may depend on the level of pre-treatment inflammation and the corresponding presence of regulatory cells and immune checkpoint molecules that normally function to prevent immune overreaction. Here, we consider two previously published cohorts of macaques who were given the immunotherapeutic N-803 to treat Simian Immunodeficiency Virus, an analog of Human Immunodeficiency Virus (HIV). One cohort had low viral loads before treatment, and N-803 temporarily suppressed viral loads. The second cohort had high viral loads that did not consistently decrease with N-803 treatment. In this work, we demonstrate with a mathematical model how these two distinct outcomes can arise due only to the different viral loads and the corresponding immune activation and regulatory response. In the model, we find that the key limiting factor is the direct inhibition of the cytotoxic action of immune cells by immune checkpoint molecules. This model indicates that simultaneous blockade of immune checkpoint molecules may be necessary for effective application of N-803 for the treatment of HIV. This and similar models can inform the design of such combination therapies for cancer and chronic infection.

systems biology↗

bioRxiv2022

Chemokine Signaling Caused by Mycobacterium avium Biofilms in the Lung Airway Increases Bacterial Loads by Spatially Diverting Macrophages

Mycobacterium avium Complex (MAC) are ubiquitous environmental biofilm-forming microbes that can colonize and infect patient lungs. Incidence and prevalence of MAC infections are increasing globally, and reinfection is common. Thus, MAC infections present a significant public health challenge. MAC infections are notoriously difficult to treat and there is an urgent need for MAC-targeted therapeutics. To identify potential drug targets, we quantify the impact of MAC biofilms and repeated exposure on infection progression using a computational model of MAC infection in lung airways. MAC biofilms aid epithelial cell invasion, cause premature macrophage apoptosis, and limit antibiotic efficacy. We develop an agent-based model that incorporates the interactions between bacteria, biofilm and immune cells. We perform virtual knockouts to quantify the effects of the sources of biofilm (biofilm simultaneously deposited with bacteria vs. formed in the airway after initial bacterial deposition), and their effects on macrophages (inducing apoptosis and slowing phagocytosis). We also quantify the effects of repeated bacterial exposure to assess the impact of reinfection on infection progression. Our results show that chemokines released by biofilm-induced apoptosis bias macrophage chemotaxis towards pockets of infected and apoptosed macrophages. This bias results in fewer macrophages finding extracellular bacteria, allowing the extracellular planktonic bacteria to replicate freely. These spatial macrophage trends are further exacerbated with repeated deposition of bacteria. Our model indicates that interventions to either abrogate macrophages apoptotic responses to bacterial biofilms and/or reduce frequency of patient exposure to bacteria will lower bacterial load, and likely overall risk of infection.

systems biology↗

bioRxiv2021

The Role of Biofilms, Bacterial Phenotypes, and Innate Immune Response in Mycobacterium avium Colonization to Infection

Mycobacterium avium complex (MAC), is known for colonizing and infecting humans following inhalation of the bacteria. MAC pulmonary disease is notoriously difficult to treat and prone to recurrence. Both the incidence and prevalence MAC pulmonary disease have been increasing globally. MAC is well known to form biofilms in the environment, and in vitro, these biofilms have been shown to aid MAC in epithelial cell invasion, protect MAC from phagocytosis, and cause premature apoptosis in macrophages. In vivo, the system of interactions between MAC, biofilms and host macrophages is complex, difficult to replicate in vitro and in animal models, has not been fully characterized. Here we present a three-dimensional agent-based model of a lung airway to help understand how these interactions evolve in the first 14 days post-bacterial inhalation. We parameterized the model using published data and performed uncertainty analysis to characterize outcomes and parameters effects on those outcomes. Model results show diverse outcomes, including wide ranges of macrophage recruitment levels, and bacterial loads and phenotype distribution. Though most bacteria are phagocytosed by macrophages and remain intracellular, there are also many simulations in which extracellular bacteria continue to drive the colonization and infection. Initial parameters dictating host immune levels, bacterial loads introduced to the airway, and biofilm conditions have significant and lasting impacts on the course of these results. Additionally, though macrophage recruitment is key for suppressing bacterial loads, there is evidence of significant excess recruitment that fail to impact bacterial numbers. These results highlight a need and identify a path for further exploration into the inhalation events in MAC infection. Early infection dynamics could have lasting impacts on the development of nodular bronchiectatic or fibrocavitary disease as well as inform possible preventative and treatment intervention targeting biofilm-macrophage interactions.

systems biology↗

bioRxiv2021

Mechanisms of phosphatidylserine influence on viral production: a computational model of Ebola virus matrix protein assembly

Ebola virus (EBOV) infections continue to pose a global public health threat, with high mortality rates and sporadic outbreaks in Central and Western Africa. A quantitative understanding of the key processes driving EBOV assembly and budding could provide valuable insights to inform drug development. Here we used a computational model to evaluate EBOV matrix assembly. Our model focused on the assembly kinetics of VP40, the matrix protein in EBOV, and its interaction with phosphatidylserine (PS) in the host cell membrane. Human cells transfected with VP40-expressing plasmids are capable of producing virus-like particles (VLPs) that closely resemble EBOV virions. We used data from this in vitro VP40 system to calibrate our computational model. PS levels in the host cell membrane had been shown to affect VP40 dynamics as well as VLP production through recruiting VP40 dimers to plasma membrane inner leaflet. Our computational results indicated that PS may have direct influence on VP40 filament growth and affect multiple steps in the assembly and budding of VP40 VLPs. We also proposed that the assembly of VP40 filaments may follow the nucleation-elongation theory where initialization and oligomerization of VP40 are two separate and distinct steps in the assembly process. This work illustrated how computational and experimental approaches can be combined to allow for additional analysis and hypothesis generation. Our findings advanced understanding of the molecular process of EBOV assembly and budding processes and may help the development of new EBOV treatments targeting VP40 matrix assembly.

systems biology↗

bioRxiv2021

The Ebola virus matrix protein clusters phosphatidylserine, a critical step in viral budding

Phosphatidylserine (PS) has been shown to be a critical lipid factor in the assembly and spread of numerous lipid enveloped viruses. Here, we describe the ability of the Ebola virus (EBOV) matrix protein eVP40 to induce clustering of PS and promote viral budding in vitro, as well as the ability of an FDA approved drug, fendiline, to reduce PS clustering subsequently reducing virus budding and entry. To gain mechanistic insight into fendiline inhibition of EBOV replication, multiple in vitro assays were employed including imaging, viral budding and viral entry assays. Fendiline reduced the PS content in mammalian cells and PS in the plasma membrane, reducing the ability of VP40 to form new virus particles. Further, particles that do form from fendiline treated cells have altered particle morphology and decreased infectivity capacity. These complementary studies reveal the mechanism by which filovirus matrix proteins cluster PS to enhance viral assembly, budding, and spread from the host cell while also laying the groundwork for fundamental drug targeting strategies.

microbiology↗

bioRxiv2020

Mathematical modeling of N-803 treatment in SIV-infected non-human primates

Immunomodulatory drugs could contribute to a functional cure for Human Immunodeficiency Virus (HIV). Interleukin-15 (IL-15) promotes expansion and activation of CD8+ T cell and natural killer (NK) cell populations. In one study, an IL-15 superagonist, N-803, suppressed Simian Immunodeficiency Virus (SIV) in non-human primates (NHPs) who had received prior SIV vaccination. However, viral suppression attenuated with continued N-803 treatment, partially returning after long treatment interruption. While there is evidence of concurrent drug tolerance, immune regulation, and viral escape, the relative contributions of these mechanisms to the observed viral dynamics have not been quantified. Here, we utilize mathematical models of N-803 treatment in SIV-infected macaques to estimate contributions of these three key mechanisms to treatment outcomes: 1) drug tolerance, 2) immune regulation, and 3) viral escape. We calibrated our model to viral and lymphocyte responses from the above-mentioned NHP study. Our models track CD8+ T cell and NK cell populations with N-803-dependent proliferation and activation, as well as viral dynamics in response to these immune cell populations. We compared mathematical models with different combinations of the three key mechanisms based on Akaike Information Criterion and important qualitative features of the NHP data. Two minimal models were capable of reproducing the observed SIV response to N-803. In both models, immune regulation strongly reduced cytotoxic cell activation to enable viral rebound. Either long-term drug tolerance or viral escape (or some combination thereof) could account for changes to viral dynamics across long breaks in N-803 treatment. Theoretical explorations with the models showed that less-frequent N-803 dosing and concurrent immune regulation blockade (e.g. PD-L1 inhibition) may improve N-803 efficacy. However, N-803 may need to be combined with other immune therapies to countermand viral escape from the CD8+ T cell response. Our mechanistic model will inform such therapy design and guide future studies. Author summaryImmune therapy may be a critical component in the functional cure for Human Immunodeficiency Virus (HIV). N-803 is an immunotherapeutic drug that activates antigen-specific CD8+ T cells of the immune system. These CD8+ T cells eliminate HIV-infected cells in order to limit the spread of infection in the body. In one study, N-803 reduced plasma viremia in macaques that were infected with Simian Immunodeficiency Virus, an analog of HIV. Here, we used mathematical models to analyze the data from this study to better understand the effects of N-803 therapy on the immune system. Our models indicated that inhibitory signals may be reversing the stimulatory effect of N-803. Results also suggested the possibilities that tolerance to N-803 could build up within the CD8+ T cells themselves and that the treatment may be selecting for virus strains that are not targeted by CD8+ T cells. Our models predict that N-803 therapy may be made more effective if the time between doses is increased or if inhibitory signals are blocked by an additional drug. Also, N-803 may need to be combined with other immune therapies to target virus that would otherwise evade CD8+ T cells.

systems biology↗