Dataset Information

Direct input of monitoring data into a mechanistic ecological model as a way to identify the phytoplankton growth-rate response to temperature variations.

ABSTRACT: We present an approach (knowledge-and-data-driven, KDD, modeling) that allows us to get closer to understanding the processes that affect the dynamics of plankton communities. This approach, based on the use of time series obtained as a result of ecosystem monitoring, combines the key features of both the knowledge-driven modeling (mechanistic models) and data-driven (DD) modeling. Using a KDD model, we reveal the phytoplankton growth-rate fluctuations in the ecosystem of the Naroch Lakes and determine the degree of phase synchronization between fluctuations in the phytoplankton growth rate and temperature variations. More specifically, we estimate a numerical value of the phase locking index (PLI), which allows us to assess how temperature fluctuations affect the dynamics of phytoplankton growth rates. Since, within the framework of KDD modeling, we directly include the time series obtained as a result of field measurements in the model equations, the dynamics of the phytoplankton growth rate obtained from the KDD model reflect the behavior of the lake ecosystem as a whole, and PLI can be considered as a holistic parameter.

SUBMITTER: Medvinsky AB

PROVIDER: S-EPMC10287759 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Direct input of monitoring data into a mechanistic ecological model as a way to identify the phytoplankton growth-rate response to temperature variations.

Medvinsky Alexander B AB Nurieva Nailya I NI Adamovich Boris V BV Radchikova Nataly P NP Rusakov Alexey V AV

Scientific reports 20230622 1

We present an approach (knowledge-and-data-driven, KDD, modeling) that allows us to get closer to understanding the processes that affect the dynamics of plankton communities. This approach, based on the use of time series obtained as a result of ecosystem monitoring, combines the key features of both the knowledge-driven modeling (mechanistic models) and data-driven (DD) modeling. Using a KDD model, we reveal the phytoplankton growth-rate fluctuations in the ecosystem of the Naroch Lakes and de ...[more]

PMID: 37349488

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Project description:Iron is an essential micronutrient and can limit the growth of both marine phytoplankton and heterotrophic bacterioplankton. In this study, we investigated the molecular basis of heme transport, an organic iron acquisition pathway, in phytoplankton-associated Roseobacter bacteria and explored the potential role of bacterial heme uptake in the marine environment. We searched 153 Roseobacter genomes and found that nearly half contained putative complete heme transport systems with nearly the same synteny. We also examined a publicly available coculture transcriptome and found that Roseobacter strain Sulfitobacter sp. strain SA11 strongly downregulated a putative heme transport gene cluster during mutualistic growth with a marine diatom, suggesting that the regulation of heme transport might be influenced by host cues. We generated a mutant of phytoplankton-associated Roseobacter strain Ruegeria sp. strain TM1040 by insertionally inactivating its homolog of the TonB-dependent heme transporter hmuR and confirmed the role of this gene in the uptake of heme and hemoproteins. We performed competition experiments between iron-limited wild-type and mutant TM1040 strains and found that the wild type maintains a growth advantage when competing with the mutant for iron compounds derived solely from lysed diatom cells. Heme transport systems were largely absent from public marine metagenomes and metatranscriptomes, suggesting that marine bacteria with the potential for heme transport likely have small standing populations in the free-living bacterioplankton. Heme transport is likely a useful strategy for phytoplankton-associated bacteria because it provides direct access to components of the host intracellular iron pool after lysis. IMPORTANCE Ecosystem productivity in large regions of the surface ocean is fueled by iron that has been microbially regenerated from biomass. Currently, the specific microbes and molecules that mediate the transfer of recycled iron between microbial trophic levels remain largely unknown. We characterized a marine bacterial heme transporter and verified its role in acquiring heme, an abundant iron-containing enzyme cofactor. We present evidence that after host cell lysis, phytoplankton-associated bacteria directly extract heme and hemoproteins from algal cellular debris in order to fulfill their iron requirements and that the regulation of this process may be modulated by host cues. Direct heme transport, in contrast to multistep extracellular processing of hemoproteins, may allow certain phytoplankton-associated bacteria to rapidly extract iron from decaying phytoplankton, thus efficiently recycling cellular iron into the wider microbial loop.

Dataset Information

Direct input of monitoring data into a mechanistic ecological model as a way to identify the phytoplankton growth-rate response to temperature variations.

Publications

Direct input of monitoring data into a mechanistic ecological model as a way to identify the phytoplankton growth-rate response to temperature variations.

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