Observing bacteria through the lens of social evolution

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
Journal of Biology 10/2008; 7(7):27. DOI: 10.1186/jbiol87
Source: PubMed

ABSTRACT Explaining the evolution of cooperative behavior is a long-standing problem for which much theory has been developed. A recent paper in BMC Biology tests central elements of this theory by manipulating a simple bacterial experimental system. This approach is useful for assessing the principles of social evolution, but we argue that more effort must be invested in the inverse problem: using social evolution theory to understand the lives of bacteria.

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Available from: Carey D Nadell, Jan 30, 2014
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    • "For additional background, readers are encouraged to see alternative reviews on the following themes: taxa descriptions (Shimkets et al., 2006; Velicer and Hillesland, 2008), secondary metabolism diversity (Weissman and Müller, 2010), A-motility evolution (Chapter 9 and Luciano et al., 2011), myxobacterial social evolution (Velicer and Hillesland, 2008; Velicer and Vos, 2009) and microbial social evolution more broadly (e.g. Foster et al., 2007; Nadell et al., 2008; Strassmann et al., 2011; Strassmann and Queller, 2011; Travisano and Velicer, 2004; Velicer and Vos, 2009; West, 2006). "
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    ABSTRACT: Recent discoveries have found the myxobacteria to be much more diverse - both across and within species - than previously known, from global to micrometer spatial scales. Evolutionary analysis of such extant diversity promises to reveal much about how myxobacteria have adapted to natural ecological habitats in the past and continue to evolve in the present, particularly with regard to their intriguing social phenotypes. Experimental populations propagated under defined laboratory conditions undergo very rapid evolution at cooperative traits in a manner that radically changes their social composition. Analysis of such experimentally evolved populations allows detailed characterization of social evolutionary dynamics in real time. Moreover, traditional genetic tools and new genome sequencing technologies together allow deep investigation of the molecular basis of adaptation by experimental populations to known ecological habitats, which in turn can lead to new discoveries regarding the molecular mechanisms governing social behavior.
    Myxobacteria: Genomics, Cellular and Molecular Biology, Edited by Zhaomin Yang, Penelope I. Higgs, 02/2014: chapter Whence Comes Social Diversity? Ecological and Evolutionary Analysis of the Myxobacteria: pages 1-28; Caister Academic Press., ISBN: 978-1908230348
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    • "Bacteria, for instance, produce, release and sense signaling molecules (so-called autoinducers) which can diffuse in the environment and are used for population coordination. This mechanism, known as quorum sensing (Miller & Bassler 2001, Nardelli et al. 2008, Ng & Bassler 2009) is believed to play a key role in bacterial infection, as well as e.g. in bioluminescence and biofilm formation (Anetzberger et al. 2009), (Nadell et al. 2008). In a neuronal context, a mechanism similar to that of quorum sensing may involve local field potentials, which may play an important role in the synchronization of clusters of neurons, (Pesaran et al. 2002, Boustani et al. 2009, Tabareau et al. 2010, Anastassiou et al. 2010). "
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    ABSTRACT: In many natural synchronization phenomena, communication between individual elements occurs not directly, but rather through the environment. One of these instances is bacterial quorum sensing, where bacteria release signaling molecules in the environment which in turn are sensed and used for population coordination. Extending this motivation to a general non- linear dynamical system context, this paper analyzes synchronization phenomena in networks where communication and coupling between nodes are mediated by shared dynamical quan- tities, typically provided by the nodes' environment. Our model includes the case when the dynamics of the shared variables themselves cannot be neglected or indeed play a central part. Applications to examples from systems biology illustrate the approach.
    Physical Review E 10/2010; 82(4 Pt 1):041919. DOI:10.1103/PhysRevE.82.041919 · 2.33 Impact Factor
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    • "Computational models of these systems are also frequently used, providing researchers complete environmental control and access to each organism [6] [8] [19]. One area in which cooperative behaviors are critical is in the formation and maintenance of biofilms [15], which are aggregates of microorganisms connected within a matrix of extracellular polymeric substance (EPS) [7]. This " stickiness " allows organisms in biofilms to cohabitate in larger densities and resist being flushed out of their environment. "
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    ABSTRACT: Understanding the evolution of cooperation as part of an evolutionary stable strategy (ESS) is a difficult problem that has been the focus of much work. The associated costs of cooperation may lower the fitness of an organism below that of its non-cooperating counterpart, allowing the more fit organism to persist and outcompete the cooperator. Insight into these behaviors can help provide a better understanding of many aspects of the natural world, as well as provide future avenues for fighting disease. In this study, we use digital evolution to examine how the abundance of a required resource affects the cooperative production of a public good in an adverse environment. Evolutionary computation is an excellent tool for examining these problems, as it offers researchers complete access to organisms and total control over their environment. We find that stable cooperation can occur in otherwise competitive environments at discrete levels corresponding to the availability of a required resource. When resource levels are low, organisms focus solely on competitive behaviors. However, once resource levels cross a critical threshold, cooperation persists in populations. Further, this cooperation occurs in patches, where it is most likely to benefit relatives. Finally, we find that in some cases this cooperative behavior allows organisms to increase their competitive abilities as well.
    Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010; 01/2010