Abstract
Blooms of marine phytoplankton fix complex pools of dissolved organic matter (DOM) that are thought to be partitioned among hundreds of heterotrophic microbes at the base of the food web. While the relationship between microbial consumers and phytoplankton DOM is a key component of marine carbon cycling, microbial loop metabolism is largely understood from model organisms and substrates. Here, we took an untargeted approach to measure and analyze partitioning of four distinct phytoplankton-derived DOM pools among heterotrophic populations in a natural microbial community using a combination of ecogenomics, stable isotope probing (SIP), and proteomics. Each 13C-labeled exudate or lysate from a diatom or a picocyanobacterium was preferentially assimilated by different heterotrophic taxa with specialized metabolic and physiological adaptations. Bacteroidetes populations, with their unique high-molecular-weight transporters, were superior competitors for DOM derived from diatom cell lysis, rapidly increasing growth rates and ribosomal protein expression to produce new relatively high C:N biomass. Proteobacteria responses varied, with relatively low levels of assimilation by Gammaproteobacteria populations, while copiotrophic Alphaproteobacteria such as the Roseobacter clade, with their diverse array of ABC- and TRAP-type transporters to scavenge monomers and nitrogen-rich metabolites, accounted for nearly all cyanobacteria exudate assimilation and produced new relatively low C:N biomass. Carbon assimilation rates calculated from SIP data show that exudate and lysate from two common marine phytoplankton are being used by taxonomically distinct sets of heterotrophic populations with unique metabolic adaptations, providing a deeper mechanistic understanding of consumer succession and carbon use during marine bloom events.
Original language | English |
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Article number | e2101178118 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 118 |
Issue number | 41 |
DOIs | |
State | Published - Oct 12 2021 |
Funding
We would like to thank Dr. Kimberly Halsey for providing phytoplankton strains and assistance with media recipes and Dr. Steven Giovannoni for use of the Guava Flow Cytometer for cell counts and for personal communication during the revision process. We also thank Oregon State University’s Center for Genome Research and Biocomputing for biomolecule data generation and computing resources and the Hatfield Marine Science Center for resource access and laboratory use. This work was funded by the Gordon and Betty Moore Foundation Marine Microbiology Initiative (Grant No. GBMF3302). Part of this work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. Oak Ridge National Laboratory resources, including the Oak Ridge Leadership Computing Facility, were used in the research and are supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725. ACKNOWLEDGMENTS. We would like to thank Dr. Kimberly Halsey for providing phytoplankton strains and assistance with media recipes and Dr. Steven Giovannoni for use of the Guava Flow Cytometer for cell counts and for personal communication during the revision process. We also thank Oregon State University’s Center for Genome Research and Biocomputing for biomolecule data generation and computing resources and the Hatfield Marine Science Center for resource access and laboratory use. This work was funded by the Gordon and Betty Moore Foundation Marine Microbiology Initiative (Grant No. GBMF3302). Part of this work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. Oak Ridge National Laboratory resources, including the Oak Ridge Leadership Computing Facility, were used in the research and are supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725.
Keywords
- Dissolved organic matter
- Microbial loop
- Phytoplankton bloom
- Proteomics SIP
- Resource partitioning