scholarly journals Which games are growing bacterial populations playing?

2015 ◽  
Vol 12 (108) ◽  
pp. 20150121 ◽  
Author(s):  
Xiang-Yi Li ◽  
Cleo Pietschke ◽  
Sebastian Fraune ◽  
Philipp M. Altrock ◽  
Thomas C. G. Bosch ◽  
...  
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Microbial Communities ◽  
Evolutionary Game Theory ◽  
Community Dynamics ◽  
Growth Parameters ◽  
Evolutionary Game ◽  
Frequency Dependent

Microbial communities display complex population dynamics, both in frequency and absolute density. Evolutionary game theory provides a natural approach to analyse and model this complexity by studying the detailed interactions among players, including competition and conflict, cooperation and coexistence. Classic evolutionary game theory models typically assume constant population size, which often does not hold for microbial populations. Here, we explicitly take into account population growth with frequency-dependent growth parameters, as observed in our experimental system. We study the in vitro population dynamics of the two commensal bacteria ( Curvibacter sp. (AEP1.3) and Duganella sp. (C1.2)) that synergistically protect the metazoan host Hydra vulgaris (AEP) from fungal infection. The frequency-dependent, nonlinear growth rates observed in our experiments indicate that the interactions among bacteria in co-culture are beyond the simple case of direct competition or, equivalently, pairwise games. This is in agreement with the synergistic effect of anti-fungal activity observed in vivo . Our analysis provides new insight into the minimal degree of complexity needed to appropriately understand and predict coexistence or extinction events in this kind of microbial community dynamics. Our approach extends the understanding of microbial communities and points to novel experiments.

scholarly journals Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations

2014 ◽  
Vol 4 (4) ◽  
pp. 20140037 ◽  
Author(s):  
David Liao ◽  
Thea D. Tlsty
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Analysis Method ◽  
Analysis Techniques ◽  
Game Theoretic ◽  
And Control

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

scholarly journals Modelling population dynamics in a unicellular social organism community using a minimal model and evolutionary game theory

Open Biology ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 200206
Author(s):  
Ravindra Garde ◽  
Jan Ewald ◽  
Ákos T. Kovács ◽  
Stefan Schuster
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Minimal Models ◽  
Unicellular Organisms ◽  
Cyclic Dynamics ◽  
High Level ◽  
Complex Phenomena ◽  
Social Organism

Most unicellular organisms live in communities and express different phenotypes. Many efforts have been made to study the population dynamics of such complex communities of cells, coexisting as well-coordinated units. Minimal models based on ordinary differential equations are powerful tools that can help us understand complex phenomena. They represent an appropriate compromise between complexity and tractability; they allow a profound and comprehensive analysis, which is still easy to understand. Evolutionary game theory is another powerful tool that can help us understand the costs and benefits of the decision a particular cell of a unicellular social organism takes when faced with the challenges of the biotic and abiotic environment. This work is a binocular view at the population dynamics of such a community through the objectives of minimal modelling and evolutionary game theory. We test the behaviour of the community of a unicellular social organism at three levels of antibiotic stress. Even in the absence of the antibiotic, spikes in the fraction of resistant cells can be observed indicating the importance of bet hedging. At moderate level of antibiotic stress, we witness cyclic dynamics reminiscent of the renowned rock–paper–scissors game. At a very high level, the resistant type of strategy is the most favourable.

Evolutionary Games and Local Dynamics

2015 ◽  
Vol 17 (02) ◽  
pp. 1540016 ◽  
Author(s):  
Philippe Uyttendaele ◽  
Frank Thuijsman
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Global Dynamics ◽  
Local Interactions ◽  
Local Dynamics

In this paper, we examine several options for modeling local interactions within the framework of evolutionary game theory. Several examples show that there is a major difference between population dynamics using local dynamics versus global dynamics. Moreover, different modeling choices may lead to very diverse results.

scholarly journals Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

2014 ◽  
Vol 4 (4) ◽  
pp. 20140038 ◽  
Author(s):  
David Liao ◽  
Thea D. Tlsty
Keyword(s):  
Population Dynamics ◽  
Computational Analysis ◽  
Evolutionary Game ◽  
Biological Knowledge ◽  
Complex Dynamic ◽  
Experimental Systems ◽  
Mathematical Equations ◽  
Therapy Design

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments.

scholarly journals Collapse of Intra-Tumor Cooperation Induced by Engineered Defector Cells

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3674
Author(s):  
Marco Archetti
Keyword(s):  
Game Theory ◽  
Growth Factors ◽  
Evolutionary Game Theory ◽  
Clonal Selection ◽  
Evolutionary Game ◽  
Cost Benefit ◽  
Cancer Therapies ◽  
Consequent Reduction ◽  
Cost Benefit Ratio

Anti-cancer therapies promote clonal selection of resistant cells that evade treatment. Effective therapy must be stable against the evolution of resistance. A potential strategy based on concepts from evolutionary game theory is to impair intra-tumor cooperation using genetically modified cells in which genes coding for essential growth factors have been knocked out. Such engineered cells would spread by clonal selection, driving the collapse of intra-tumor cooperation and a consequent reduction in tumor growth. Here, I test this idea in vitro in four cancer types (neuroendocrine pancreatic cancer, mesothelioma, lung adenocarcinoma and multiple myeloma). A reduction, or even complete eradication, of the producer clone and the consequent reduction in cell proliferation, is achieved in some but not all cases by introducing a small fraction of non-producer cells in the population. I show that the collapse of intra-tumor cooperation depends on the cost/benefit ratio of growth factor production. When stable cooperation among producer and non-producer cells occurs, its collapse can be induced by increasing the number of growth factors available to the cells. Considerations on nonlinear dynamics in the framework of evolutionary game theory explain this as the result of perturbation of the equilibrium of a system that resembles a public goods game, in which the production of growth factors is a cooperative phenotype. Inducing collapse of intra-tumor cooperation by engineering cancer cells will require the identification of growth factors that are essential for the tumor and that have a high cost of production for the cell.

Sign in / Sign up

Export Citation Format

Share Document