Seeing through the gray box: an integrated approach to physiological modeling ofphytoplankton stoichiometry
The‘black boxes’ of ecological stoichiometry, planktonic microbes, have longbeen recognized to have considerable effects on global biogeochemical cycles.Signi cant progress has been made in studying these effects and expanding ourunderstanding of microbial stoichiometry. However, the‘black box’ has...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:dnet:ubarcelona__::94846986cd713680095f455529cee762 |
| Acceso en línea: | https://hdl.handle.net/2445/229496 |
| Access Level: | acceso abierto |
| Palabra clave: | Cicles biogeoquímics Microbiologia marina Biogeochemical cycles Marine microbiology |
| Sumario: | The‘black boxes’ of ecological stoichiometry, planktonic microbes, have longbeen recognized to have considerable effects on global biogeochemical cycles.Signi cant progress has been made in studying these effects and expanding ourunderstanding of microbial stoichiometry. However, the‘black box’ has not beencompletely cracked open; there remain gaps in our knowledge of the fate ofelements within the phytoplankton cell, and the effect of external processes onnutrient uxes through their metabolism and into macromolecules and biomass -the eponymous‘gray box’. In this review paper, we describe the development of anintegrative modeling approach that involves a stoichiometrically explicit model ofMacromolecular Allocation and Genome-scale Metabolic Analysis (MAGMA) togain insights into the intra- and extracellular fluxes of nutrients using thecyanobacterium <em>Parasynechococcus marenigrum</em> WH8102 as a target modelorganism. We then describe an example of the genome-scale resources for P.marenigrum that can be used to build such an integrated modeling tool to seethrough the gray box of phytoplankton stoichiometry and improve ourunderstanding of the effects of resource supplies and other environmentaldrivers, especially temperature, on C:N:P demand, acquisition, and allocation atthe cellular level. |
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