ArticleCurrent research in microbial sciences2022
Modeling the elemental stoichiometry and silicon accumulation in diatoms.
Article in Current research in microbial sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Silica-Biomacromolecule Interactions: Toward a Mechanistic Understanding of Silicification.Biomacromolecules · 2025Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diatoms are important microorganisms involved in global primary production, nutrient cycling, and carbon sequestration. A unique feature of diatoms is their silica frustules, which impact sinking speed, defense against predators and viruses, and growth cycling. Thus, frustules are inherently linked to their role in ecosystems and biogeochemical cycles. However, constraints on cellular silicon levels remain unclear and few existing models resolve diatom elemental stoichiometry to specifically include variable silicon levels. Here, we use a coarse-grained model of the diatom, Thalassiosira pseudonana, compared with laboratory results to illustrate the relationship of silicon uptake with elemental stoichiometry of other nutrients. The model-data comparison suggests the balance between growth rate and silicon uptake constrains the amount of cellular silicon. Additionally, it expresses relationships between silicon, nitrogen, phosphorus, and carbon to changing growth rates in nitrogen-limited and phosphorus-limited regimes. First, our model-data comparison suggests Si uptake hits a maximum cellular quota at low growth rates and below this maximum there is independent Si uptake. In each nutrient regime, Si:N, Si:P, and Si:C decrease exponentially with growth rate when Si is below the maximum limit. This is explained by independent Si uptake and increased loss of Si to new cells. These results provide predictions of diatom stoichiometry and allocation, which can be used in ecosystem models to differentiate phytoplankton types to better represent diatoms' contribution to global biogeochemical cycles and ecosystems.
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