ArticleFrontiers in microbiology2020
A Mechanistic Model of Macromolecular Allocation, Elemental Stoichiometry, and Growth Rate in Phytoplankton.
Article in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Diverse biophysical and molecular mechanisms drive phytoplankton sinking in response to starvation.PLoS biology · 2025Article
- Metabolic biochemical models of NmSystems · 2025Article
- The effect of temperature on phytoplankton physiology: a mesocosm and modeling study.Microbiology spectrum · 2025Article
- Biophysical and molecular mechanisms responsible for phytoplankton sinking in response to starvation.bioRxiv : the preprint server for biology · 2025Article
- Nitrogen and phosphorus differentially control marine biomass production and stoichiometry.Nature communications · 2025Article
- Latitudinal patterns in ocean C:N:P reflect phytoplankton acclimation and macromolecular composition.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Saturating growth rate against phosphorus concentration explained by macromolecular allocation.mSystems · 2023Article
- Coexistence of Dominant Marine Phytoplankton Sustained by Nutrient Specialization.Microbiology spectrum · 2023Article
- The balance between photosynthesis and respiration explains the niche differentiation betweenComputational and structural biotechnology journal · 2023Article
- Single-cell measurements and modelling reveal substantial organic carbon acquisition by Prochlorococcus.Nature microbiology · 2022Article
- Adaptive carbon export response to warming in the Sargasso Sea.Nature communications · 2022Article
- Modeling the elemental stoichiometry and silicon accumulation in diatoms.Current research in microbial sciences · 2022Article
- Global patterns in marine organic matter stoichiometry driven by phytoplankton ecophysiology.Nature geoscience · 2022Article
- Saturating relationship between phytoplankton growth rate and nutrient concentration explained by macromolecular allocation.Current research in microbial sciences · 2022Article
- QuantifyingComputational and structural biotechnology journal · 2021Article
- Modeled temperature dependencies of macromolecular allocation and elemental stoichiometry in phytoplankton.Computational and structural biotechnology journal · 2021Article
- Quantitative models of nitrogen-fixing organisms.Computational and structural biotechnology journal · 2020Review
- The ongoing need for rates: can physiology and omics come together to co-design the measurements needed to understand complex ocean biogeochemistry?Journal of plankton researchReview
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a model of the growth rate and elemental stoichiometry of phytoplankton as a function of resource allocation between and within broad macromolecular pools under a variety of resource supply conditions. The model is based on four, empirically-supported, cornerstone assumptions: that there is a saturating relationship between light and photosynthesis, a linear relationship between RNA/protein and growth rate, a linear relationship between biosynthetic proteins and growth rate, and a constant macromolecular composition of the light-harvesting machinery. We combine these assumptions with statements of conservation of carbon, nitrogen, phosphorus, and energy. The model can be solved algebraically for steady state conditions and constrained with data on elemental stoichiometry from published laboratory chemostat studies. It interprets the relationships between macromolecular and elemental stoichiometry and also provides quantitative predictions of the maximum growth rate at given light intensity and nutrient supply rates. The model is compatible with data sets from several laboratory studies characterizing both prokaryotic and eukaryotic phytoplankton from marine and freshwater environments. It is conceptually simple, yet mechanistic and quantitative. Here, the model is constrained only by elemental stoichiometry, but makes predictions about allocation to measurable macromolecular pools, which could be tested in the laboratory.
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