Theoretical Computer Science - Natural computing
Island Model genetic Algorithms and Linearly Separable Problems
Selected Papers from AISB Workshop on Evolutionary Computing
System architecture for wireless sensor networks
System architecture for wireless sensor networks
Theoretical Computer Science
Evolution of Cooperative Information Gathering in Self-Replicating Digital Organisms
SASO '07 Proceedings of the First International Conference on Self-Adaptive and Self-Organizing Systems
Computer
Cooperative network construction using digital germlines
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolution of Adaptive Population Control in Multi-agent Systems
SASO '08 Proceedings of the 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Evolving quorum sensing in digital organisms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolution of Probabilistic Consensus in Digital Organisms
SASO '09 Proceedings of the 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Evolution of an adaptive sleep response in digital organisms
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Evolving cooperative, energy-conserving, agent-base systems
Evolving cooperative, energy-conserving, agent-base systems
An environment aware p-system model of quorum sensing
CiE'05 Proceedings of the First international conference on Computability in Europe: new Computational Paradigms
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Quorum sensing (QS) is a collective behavior whereby actions of individuals depend on the density of the surrounding population. Bacteria use QS to trigger secretion of digestive enzymes, formation and destruction of biofilms, and, in the case of pathogenic organisms, expression of virulence factors that cause disease. Investigations of mechanisms that prevent or disrupt QS, referred to as quorum quenching, are of interest because they provide a new alternative to antibiotics for treating bacterial infections. Traditional antibiotics either kill bacteria or inhibit their growth, producing selective pressures that promote resistant strains. In contrast, quorum quenching and other so-called anti-infective strategies focus on altering behavior. In this article we evolve QS in populations of digital organisms, a type of self-replicating computer program, and investigate the effects of quorum quenching on these populations. Specifically, we injected the populations with mutant organisms that were impaired in selected ways to disrupt the QS process. The experimental results indicate that the rate at which these mutants are introduced into a population influences both the evolvability of QS and the persistence of an existing QS behavior. Surprisingly, we also observed resistance to quorum quenching. Effectively, populations evolved resistance by reaching quorum at lower cell densities than did the parent strain. Moreover, the level of resistance was highest when the rate of mutant introduction increased over time. These results show that digital organisms can serve as a model to study the evolution and disruption of QS, potentially informing wet-lab studies aimed at identifying targets for anti-infective development.