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Updated: Aug 18, 2026
Invasion of Human Cells by a Bacterial Pathogen
Published on: March 21, 2011
Spatial invasion by a mutant pathogen
1Department of Mathematics, University of Idaho, Moscow ID 83844-1103, USA.
Abstract:
Imagine a pathogen that is spreading radially as a circular wave through a population of susceptible hosts. In the interior of this circular region, the infection dies out due to a subcritical density of susceptibles. If a mutant pathogen, having some advantage over wild-type pathogens, arises in this region it is likely to die out without leaving a noticeable trace. Mutants that arise closer to the infection wavefront have access to more susceptible hosts and thus are more likely to become established and perhaps (locally) out-compete the original pathogen. Among the factors (position, transmission rate, pathogen-induced death rate) that influence the fate of a mutant, which are most important? What does this tell us about the types of mutants that are likely to invade and become established? How do such tendencies serve to steer the evolution of pathogens in a spatial setting? Do different types of models of the same phenomena lead to similar conclusions? We address these issues from the point of view of an individual-based stochastic spatial model of host-pathogen interactions. We consider the probability of a successful invasion by a single mutant as a function of the transmissibility and virulence strengths and the mutant position in the wavefront. Next, for a version of the model in which mutations arise spontaneously, we obtain analytical and simulation results on the mean time to a successful invasion. We also use our model predictions to gain insight into experimental data on bacteriophage plaques. Finally, we compare our results to those based on ordinary and partial differential equations to better understand how different models might influence our predictions on the fate of a mutant pathogen.
Insights
A mutant pathogen is more likely to spread if it arises near the infection wavefront, not in the depleted interior. This spatial position is crucial for mutant establishment and pathogen evolution.
Area of Science:
- Evolutionary biology
- Epidemiology
- Mathematical modeling
Background:
- Pathogen spread often occurs in waves, creating spatial gradients in host availability.
- Mutant pathogens arising within an established infection may face low host densities and fail to establish.
- The spatial location of a mutant's origin significantly impacts its survival and potential to outcompete wild-type pathogens.
Purpose of the Study:
- To investigate the key factors influencing the establishment and spread of mutant pathogens in a spatially structured host population.
- To determine the relative importance of mutant position, transmissibility, and virulence in successful invasion.
- To understand how spatial dynamics shape pathogen evolution and compare predictions from different modeling approaches.
Main Methods:
- Development and analysis of an individual-based stochastic spatial model of host-pathogen interactions.
- Calculation of mutant invasion probability based on transmissibility, virulence, and position within the wavefront.
- Analytical and simulation studies of the mean time to successful invasion for spontaneously arising mutants.
- Comparison of model predictions with experimental data on bacteriophage plaque expansion.
- Evaluation of model outcomes against predictions from ordinary and partial differential equation models.
Main Results:
- Mutant pathogen invasion probability is strongly dependent on its position relative to the infection wavefront, with origins nearer the front being more successful.
- Transmissibility and virulence are critical factors, but their impact is modulated by the mutant's spatial location.
- The spatial position of origin is a primary determinant for mutant establishment, influencing evolutionary trajectories.
- The individual-based model provides insights consistent with experimental bacteriophage data.
- Discrepancies and similarities were observed when comparing results from stochastic spatial models with deterministic differential equation models.
Conclusions:
- Spatial structure is a critical determinant of mutant pathogen success and evolutionary dynamics.
- Mutants arising in resource-rich (high host density) areas, like the infection wavefront, are favored.
- The choice of modeling approach (stochastic individual-based vs. deterministic differential equations) can influence predictions about pathogen evolution.
- Understanding spatial effects is crucial for predicting pathogen emergence and evolution.
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