@article{1d31240ea7db44caacb0fd300957af36,
title = "Streamlined and abundant bacterioplankton thrive in functional cohorts",
abstract = "While fastidious microbes can be abundant and ubiquitous in their natural communities, many fail to grow axenically in laboratories due to auxotrophies or other dependencies. To overcome auxotrophies, these microbes rely on their surrounding cohort. A cohort may consist of kin (ecotypes) or more distantly related organisms (community) with the cooperation being reciprocal or nonreciprocal and expensive (Black Queen hypothesis) or costless (by-product). These metabolic partnerships (whether at single species population or community level) enable dominance by and coexistence of these lineages in nature. Here we examine the relevance of these cooperation models to explain the abundance and ubiquity of the dominant fastidious bacterioplankton of a dimictic mesotrophic freshwater lake. Using both culture-dependent (dilution mixed cultures) and culture-independent (small subunit [SSU] rRNA gene time series and environmental metagenomics) methods, we independently identified the primary cohorts of actinobacterial genera “Candidatus Planktophila” (acI-A) and “Candidatus Nanopelagicus” (acI-B) and the proteobacterial genus “Candidatus Fonsibacter” (LD12). While “Ca. Planktophila” and “Ca. Fonsibacter” had no correlation in their natural habitat, they have the potential to be complementary in laboratory settings. We also investigated the bifunctional catalase-peroxidase enzyme KatG (a common good which “Ca. Planktophila” is dependent upon) and its most likely providers in the lake. Further, we found that while ecotype and community cooperation combined may explain “Ca. Planktophila” population abundance, the success of “Ca. Nanopelagicus” and “Ca. Fonsibacter” is better explained as a community by-product. Ecotype differentiation of “Ca. Fonsibacter” as a means of escaping predation was supported but not for overcoming auxotrophies. IMPORTANCE This study examines evolutionary and ecological relationships of three of the most ubiquitous and abundant freshwater bacterial genera: “Ca. Planktophila” (acI-A), “Ca. Nanopelagicus” (acI-B), and “Ca. Fonsibacter” (LD12). Due to high abundance, these genera might have a significant influence on nutrient cycling in freshwaters worldwide, and this study adds a layer of understanding to how seemingly competing clades of bacteria can coexist by having different cooperation strategies. Our synthesis ties together network and ecological theory with empirical evidence and lays out a framework for how the functioning of populations within complex microbial communities can be studied.",
keywords = "Actinobacteria, Alphaproteobacteria, Aquatic, Bacterioplankton, Common goods, Ecology, Evolution, Metagenomics, Microbial communities, Networks",
author = "Rhiannon Mondav and Stefan Bertilsson and Moritz Buck and Silke Langenheder and Lindstr{\"o}m, {Eva S.} and Garcia, {Sarahi L.}",
note = "Funding Information: R.M., sequencing of the metagenomes, and publication were supported by grants in 2014 and 2015 from the Malm{\'e}ns Stiftelsen. S.L.G., sequencing of the mixed cultures were supported by a SciLifeLab Fellowship, and Kungl. Vetenskapsakademiens stiftelser grant BS2017-0044, Alexander Eiler{\textquoteright}s Swedish Research Council (VR) grant 2012-4592, and Lars Tranvik{\textquoteright}s Knut and Alice Wallenberg Foundation grant KAW 2013.0091. S.B. was supported by grants from the Swedish Research Council (VR) and the Swedish Research Council Formas. The sequencing of the Lake Erken 16S rRNA time series data set and chemical data was supported by the Swedish Infrastructure for Ecosystem Science (SITES). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. We gratefully acknowledge the computing resources provided by SNIC through the Uppsala Multidisciplinary Centre for Advanced Computational Science (UPPMAX) under UPPNEX projects 2015047, 2016272, and 2017147 and sequencing infrastructure support from the SciLifeLab National Genomics Infrastructure. Funding Information: R.M., sequencing of the metagenomes, and publication were supported by grants in 2014 and 2015 from the Malm?ns Stiftelsen. S.L.G., sequencing of the mixed cultures were supported by a SciLifeLab Fellowship, and Kungl. Vetenskapsakademiens stiftelser grant BS2017-0044, Alexander Eiler's Swedish Research Council (VR) grant 2012-4592, and Lars Tranvik's Knut and Alice Wallenberg Foundation grant KAW 2013.0091. S.B. was supported by grants from the Swedish Research Council (VR) and the Swedish Research Council Formas. The sequencing of the Lake Erken 16S rRNA time series data set and chemical data was supported by the Swedish Infrastructure for Ecosystem Science (SITES). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. We gratefully acknowledge the computing resources provided by SNIC through the Uppsala Multidisciplinary Centre for Advanced Computational Science (UPPMAX) under UPPNEX projects 2015047, 2016272, and 2017147 and sequencing infrastructure support from the SciLifeLab National Genomics Infrastructure. The sequencing of the Lake Erken 16S rRNA time series data set and chemical data was done with technical assistance from Omneya Ahmed, Pilar Lopez Hernandez, Helena Enderskog, Erika Bridell, and Kristiina Mustonen. S.B., S.L., E.S.L., and R.M. contributed to the genomic sampling design, organization, and selection. S.L.G. and M.B. designed and implemented the mixed-culture experiments. R.M. designed and performed the bioinformatic analyses. R.M. and S.L.G. synthesized the conceptual framework which was drafted by R.M. in consultation with S.L.G., with editorial contributions from all authors. Publisher Copyright: Copyright {\textcopyright} 2020 Mondav et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.",
year = "2020",
month = oct,
doi = "10.1128/mSystems.00316-20",
language = "English",
volume = "5",
journal = "mSystems",
issn = "2379-5077",
publisher = "American Society for Microbiology",
number = "5",
}