The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Public good dynamics drive evolution of iron acquisition strategies in natural bacterioplankton populations
Open accessAbstract
A common strategy among microbes living in iron-limited environments is the secretion of siderophores, which can bind poorly soluble iron and make it available to cells via active transport mechanisms. Such siderophore–iron complexes can be thought of as public goods that can be exploited by local communities and drive diversification, for example by the evolution of “cheating.” However, it is unclear whether bacterial populations in the environment form stable enough communities such that social interactions significantly impact evolutionary dynamics. Here we show that public good games drive the evolution of iron acquisition strategies in wild populations of marine bacteria. We found that within nonclonal but ecologically cohesive genotypic clusters of closely related Vibrionaceae, only an intermediate percentage of genotypes are able to produce siderophores. Nonproducers within these clusters exhibited selective loss of siderophore biosynthetic pathways, whereas siderophore transport mechanisms were retained, suggesting that these nonproducers can act as cheaters that benefit from siderophore producers in their local environment. In support of this hypothesis, these nonproducers in iron-limited media suffer a significant decrease in growth, which can be alleviated by siderophores, presumably owing to the retention of transport mechanisms. Moreover, using ecological data of resource partitioning, we found that cheating coevolves with the ecological specialization toward association with larger particles in the water column, suggesting that these can harbor stable enough communities for dependencies among organisms to evolve.
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Cites
Phylogenies and the Comparative Method
Felsenstein, J. (1985) · The American Naturalist · doi:10.1086/284325 · Cited by 9,793
Siderophore-Based Iron Acquisition and Pathogen Control
Miethke, M., & Marahiel, M. A. (2007) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00012-07 · Cited by 1,774
Iron Metabolism in Pathogenic Bacteria
Ratledge, C., & Dover, L. G. (2000) · Annual Review of Microbiology · doi:10.1146/annurev.micro.54.1.881 · Cited by 1,539
Cooperation and competition in pathogenic bacteria
Griffin, A. S., West, S. A., & Buckling, A. (2004) · Nature · doi:10.1038/nature02744 · Cited by 1,104
Dale, S. E., Doherty-Kirby, A., Lajoie, G., & Heinrichs, D. E. (2004) · Infection and Immunity · doi:10.1128/iai.72.1.29-37.2004 · Cited by 232
Cited by
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Mukherjee, S., & Bassler, B. L. (2019) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0186-5 · Cited by 1,374
Bacterial siderophores in community and host interactions
Kramer, J., Özkaya, Ö., & Kümmerli, R. (2020) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0284-4 · Cited by 998
Host lifestyle affects human microbiota on daily timescales
David, L. A., Materna, A. C., Friedman, J., Campos-Baptista, M. I., Blackburn, M. C., Perrotta, A., Erdman, S. E., & Alm, E. J. (2014) · Genome biology · doi:10.1186/gb-2014-15-7-r89 · Cited by 950
Competition for iron drives phytopathogen control by natural rhizosphere microbiomes
Gu, S., Wei, Z., Shao, Z., Friman, V.-P., Cao, K., Yang, T., Kramer, J., Wang, X., Li, M., Mei, X., et al. (2020) · Nature Microbiology · doi:10.1038/s41564-020-0719-8 · Cited by 544
Microbial interactions lead to rapid micro-scale successions on model marine particles
Datta, M. S., Sliwerska, E., Gore, J., Polz, M. F., & Cordero, O. X. (2016) · Nature Communications · doi:10.1038/ncomms11965 · Cited by 432
Self-citation
Metadata
- Authors
- Cordero, O. X., Ventouras, L.-A., DeLong, E. F., & Polz, M. F.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2012-11-19
- Volume
- 109
- Issue
- 49
- Pages
- 20059-20064
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2049655406
- Cited by
- 341
- References
- 5
- FWCI
- 57.10
- Type
- journal article
- Language
- en
- Open access
- green
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- Cordero, O. X., Ventouras, L.-A., DeLong, E. F., & Polz, M. F. (2012). Public good dynamics drive evolution of iron acquisition strategies in natural bacterioplankton populations. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1213344109
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