Evolving quorum sensing in digital organisms

For centuries it was thought that bacteria live asocial lives. However, recent discoveries show many species of bacteria communicate in order to perform tasks previously thought to be limited to multicellular organisms. Central to this capability is quorum sensing, whereby organisms detect cell density and use this information to trigger group behaviors. Quorum sensing is used by bacteria in the formation of biofilms, secretion of digestive enzymes and, in the case of pathogenic bacteria, release of toxins or other virulence factors. Indeed, methods to disrupt quorum sensing are currently being investigated as possible treatments for numerous diseases, including cystic fibrosis, epidemic cholera, and methicillin-resistant Staphylococcus aureus. In this paper we demonstrate the evolution of a quorum sensing behavior in populations of digital organisms. Specifically, we show that digital organisms are capable of evolving a strategy to collectively suppress self-replication, when the population density reaches a specific, evolved threshold. We present the evolved genome of an organism exhibiting this behavior and analyze the collective operation of this “algorithm. ” Finally, through a set of experiments we demonstrate that the behavior scales to populations up to 400 times larger than those in which the behavior evolved

More Bang For Your Buck: Quorum-Sensing Capabilities Improve the Efficacy of Suicidal Altruism

Within the context of evolution, an altruistic act that benefits the receiving individual at the expense of the acting individual is a puzzling phenomenon. An extreme form of altruism can be found in colicinogenic E. coli. These suicidal altruists explode, releasing colicins that kill unrelated individuals, which are not colicin resistant. By committing suicide, the altruist makes it more likely that its kin will have less competition. The benefits of this strategy rely on the number of competitors and kin nearby. If the organism explodes at an inopportune time, the suicidal act may not harm any competitors. Communication could enable organisms to act altruistically when environmental conditions suggest that that strategy would be most beneficial. Quorum sensing is a form of communication in which bacteria produce a protein and gauge the amount of that protein around them. Quorum sensing is one means by which bacteria sense the biotic factors around them and determine when to produce products, such as antibiotics, that influence competition. Suicidal altruists could use quorum sensing to determine when exploding is most beneficial, but it is challenging to study the selective forces at work in microbes. To address these challenges, we use digital evolution (a form of experimental evolution that uses self-replicating computer programs as organisms) to investigate the effects of enabling altruistic organisms to communicate via quorum sensing. We found that quorum-sensing altruists killed a greater number of competitors per explosion, winning competitions against non-communicative altruists. These findings indicate that quorum sensing could increase the beneficial effect of altruism and the suite of conditions under which it will evolve.Comment: 8 pages, 8 figures, ALIFE '14 conferenc

Contextual organismality: Beyond pattern to process in the emergence of organisms

Biologists have taken the concept of organism largely for granted. However, advances in the study of chimerism, symbiosis, bacterial-eukaryote associations, and microbial behavior have prompted a redefinition of organisms as biological entities exhibiting low conflict and high cooperation among their parts. This expanded view identifies organisms in evolutionary time. However, the ecological processes, mechanisms, and traits that drive the formation of organisms remain poorly understood. Recognizing that organismality can be context dependent, we advocate elucidating the ecological contexts under which entities do or do not act as organisms. Here we develop a "contextual organismality" framework and provide examples of entities, such as honey bee colonies, tumors, and bacterial swarms, that can act as organisms under specific life history, resource, or other ecological circumstances. We suggest that context dependence may be a stepping stone to the development of increased organismal unification, as the most integrated biological entities generally show little context dependence. Recognizing that organismality is contextual can identify common patterns and testable hypotheses across different entities. The contextual organismality framework can illuminate timeless as well as pressing issues in biology, including topics as disparate as cancer emergence, genomic conflict, evolution of symbiosis, and the role of the microbiota in impacting host phenotype.John Templeton FoundationVersion of record online: 27 October 2016; published open access.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A systematic approach to cancer: evolution beyond selection.

Cancer is typically scrutinized as a pathological process characterized by chromosomal aberrations and clonal expansion subject to stochastic Darwinian selection within adaptive cellular ecosystems. Cognition based evolution is suggested as an alternative approach to cancer development and progression in which neoplastic cells of differing karyotypes and cellular lineages are assessed as self-referential agencies with purposive participation within tissue microenvironments. As distinct self-aware entities, neoplastic cells occupy unique participant/observer status within tissue ecologies. In consequence, neoplastic proliferation by clonal lineages is enhanced by the advantaged utilization of ecological resources through flexible re-connection with progenitor evolutionary stages

Description and composition of bio-inspired design patterns: a complete overview

In the last decade, bio-inspired self-organising mechanisms have been applied to different domains, achieving results beyond traditional approaches. However, researchers usually use these mechanisms in an ad-hoc manner. In this way, their interpretation, definition, boundary (i.e. when one mechanism stops, and when another starts), and implementation typically vary in the existing literature, thus preventing these mechanisms from being applied clearly and systematically to solve recurrent problems. To ease engineering of artificial bio-inspired systems, this paper describes a catalogue of bio-inspired mechanisms in terms of modular and reusable design patterns organised into different layers. This catalogue uniformly frames and classifies a variety of different patterns. Additionally, this paper places the design patterns inside existing self-organising methodologies and hints for selecting and using a design patter