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      Siderophore cheating and cheating resistance shape competition for iron in soil and freshwater Pseudomonas communities

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      Nature Communications
      Nature Publishing Group UK

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          Abstract

          All social organisms experience dilemmas between cooperators performing group-beneficial actions and cheats selfishly exploiting these actions. Although bacteria have become model organisms to study social dilemmas in laboratory systems, we know little about their relevance in natural communities. Here, we show that social interactions mediated by a single shareable compound necessary for growth (the iron-scavenging pyoverdine) have important consequences for competitive dynamics in soil and pond communities of Pseudomonas bacteria. We find that pyoverdine non- and low-producers co-occur in many natural communities. While non-producers have genes coding for multiple pyoverdine receptors and are able to exploit compatible heterologous pyoverdines from other community members, producers differ in the pyoverdine types they secrete, offering protection against exploitation from non-producers with incompatible receptors. Our findings indicate that there is both selection for cheating and cheating resistance, which could drive antagonistic co-evolution and diversification in natural bacterial communities.

          Abstract

          Lab strains of Pseudomonas are model systems for the evolution of cooperation over public goods (iron-scavenging siderophores). Here, Butaitė et al. add ecological and evolutionary insight into this system by showing that cheating and resistance to cheating both shape competition for iron in natural Pseudomonas communities.

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          Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

          The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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            Chemistry and biology of siderophores.

            Siderophores are compounds produced by bacteria, fungi and graminaceous plants for scavenging iron from the environment. They are low-molecular-weight compounds (500-1500 daltons) possessing a high affinity for iron(III) (Kf > 1030), the biosynthesis of which is regulated by iron levels and the function of which is to supply iron to the cell. This article briefly describes the classification and chemical properties of siderophores, before outlining research on siderophore biosynthesis and transport. Clinically important siderophores and the therapeutic potential of siderophore design are described. Appendix 1 provides a comprehensive list of siderophore structures.
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              Social evolution theory for microorganisms.

              Microorganisms communicate and cooperate to perform a wide range of multicellular behaviours, such as dispersal, nutrient acquisition, biofilm formation and quorum sensing. Microbiologists are rapidly gaining a greater understanding of the molecular mechanisms involved in these behaviours, and the underlying genetic regulation. Such behaviours are also interesting from the perspective of social evolution - why do microorganisms engage in these behaviours given that cooperative individuals can be exploited by selfish cheaters, who gain the benefit of cooperation without paying their share of the cost? There is great potential for interdisciplinary research in this fledgling field of sociomicrobiology, but a limiting factor is the lack of effective communication of social evolution theory to microbiologists. Here, we provide a conceptual overview of the different mechanisms through which cooperative behaviours can be stabilized, emphasizing the aspects most relevant to microorganisms, the novel problems that microorganisms pose and the new insights that can be gained from applying evolutionary theory to microorganisms.
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                Author and article information

                Contributors
                elena.butaite@gmail.com
                rolf.kuemmerli@uzh.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                4 September 2017
                4 September 2017
                2017
                : 8
                : 414
                Affiliations
                ISNI 0000 0004 1937 0650, GRID grid.7400.3, Department of Plant and Microbial Biology, , University of Zurich, ; Winterthurerstrasse 190, 8057 Zurich, Switzerland
                Author information
                http://orcid.org/0000-0003-4084-6679
                Article
                509
                10.1038/s41467-017-00509-4
                5583256
                28871205
                358586d5-04a6-460e-836d-00f9e5118dc9
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2016
                : 29 June 2017
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