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Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session E

Poster M3 - Quantifying the Intercellular Mechanisms of Ebolavirus transmission using Multi-scale Agent-based Model

Saturday, October 26, 2024
10:00 AM - 11:00 AM EST
Location: Exhibit Hall E, F & G

Introduction:  Ebola Virus Disease (EVD) is caused by an Ebolavirus (EBOV) infection and is associated with fatal hemorrhagic fever. It has caused more than 30 outbreaks, some with 100% mortality. The genome of EBOV is simple, with only seven monocistronic genes, leading to an intricate cycle of infection. There is a gap in our knowledge of the protein-protein and lipid-protein interactions that drive effective viral production and cell-to-cell spread making it challenging to develop therapies. Experimental research with live EBOV is limited due to the requirement of BSL-4 laboratories. To enable EBOV life cycle studies in lower safety level laboratories, subsets of EBOV genes have been inserted into plasmids and expressed separately or together in transfected cells. Matrix protein VP40, when expressed independently, can produce virus-like particles (VLPs) with similar size, shape, entry, and cell attachment properties as EBOV virions. The production of VLPs is enhanced when VP40 is co-expressed together with NP, nucleoprotein, which forms NP inclusions that are encapsulated in the VP40 VLP matrix. This interaction between VP40 and NP to produce VLPs has been quantified in individual cells with a subcellular differential equation model. Here, we employ this existing data to develop a multi-scale Agent-based model to represent the VP40-NP system in a population of cells to elucidate how single-cell VP40 and NP interactions propagate across a population of cells to sustain robust viral proliferation.

Materials and

Methods:  A spatiotemporal Agent-Based simulation of in vitro Ebolavirus infection is developed using a cross-platform Java-based modeling system called Repast Simphony. A 100 x 100 x 10 (x, y, z) dimensional grid represents part of the in-vitro culture where each grid compartment is 1 m3. There are five agent types in the model which are Transfected Kidney cells, IB-free-VLP (no NP inclusions), IB-containing-VLP (with NP inclusions) Healthy Kidney cells, and VLP-entered cells. Kidney cells are assumed to be adherent. VLP's have movement via Brownian motion. VLP agents are budded from Transfected Kidney cells and enter Healthy Kidney cells through contact. The VLP production rate by each cell is defined by the existing subcellular Ordinary Differential Equation (ODE) model. The simulation represents 3 days of real-time in-vitro experiments. Parameter values and initial conditions are based on existing literature.

Results, Conclusions, and Discussions: The intercellular model simulates the mechanism of VLP budding by transfected cells and the first round of VLP entry into Healthy cells. The previously developed subcellular model predicted at least a 3-fold increase in the VLP production in the NP-VP40 system compared to the VP40-only system over a 50-hour time course. The multi-scale model integrates the intercellular and subcellular models, representing a cell population. The subcellular model identified 50 calibrated parameter sets. In the multi-cellular model, each cell is randomly assigned one of the 50 calibrated parameter sets, and the corresponding subcellular model results define the production of VLP by that cell. The multi-scale model can successfully produce VLPs based on the subcellular data and their distributions are in correspondence with each other. Unlike the VP40-only system, the NP-VP40 system produces two types of VLPs, one with NP inclusions (IB-containing-VLP) and the other without NP inclusions (IB-free-VLP). NP is a critical component of nucleocapsid of EBOV and has complex interactions with VP40 matrix protein accounting for the increase in the VLP production. IB-free-VLP is similar to the original VP40-only VLP and the production of IB-containing-VLP also by NP-VP40 system contributes majorly to this increase. We quantified the number and type of VLPs that enter Healthy Kidney cells in a population of cells stochastically. Results suggest that irrespective of the type of VLP produced, their entry into a healthy cell is defined primarily by the number of VLPs in the environment.

This study introduces a novel framework of multi-scale Agent-based modeling in the context of computational virology. The findings provide valuable insights into key mechanisms of EBOV transmission and spread, connecting the cellular level to the molecular level (proteins and lipids) which is crucial in identifying drug targets. Its potential to build upon and recreate to understand other diseases underscores its broader societal impact.

Acknowledgements (Optional):