ArticleBMC systems biology2011
Microarray data can predict diurnal changes of starch content in the picoalga Ostreococcus.
Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 38 citations in OpenAlex.
- Multiomics integration unveils photoperiodic plasticity in the molecular rhythms of marine phytoplankton.The Plant cell · 2025Article
- Circadian regulation of metabolism across photosynthetic organisms.The Plant journal : for cell and molecular biology · 2023Review
- Biocatalytic quantification of α-glucan in marine particulate organic matter.MicrobiologyOpen · 2022Article
- CBM20CP, a novel functional protein of starch metabolism in green algae.Plant molecular biology · 2022Article
- Selection and validation of reference genes for quantitative real-time PCR in the green microalgae Tetraselmis chui.PloS one · 2021Article
- A curated genome-scale metabolic model of Bordetella pertussis metabolism.PLoS computational biology · 2017Article
- Metabolic profiling identifies trehalose as an abundant and diurnally fluctuating metabolite in the microalgaMetabolomics : Official journal of the Metabolomic Society · 2017Article
- Evolution of Daily Gene Co-expression Patterns from Algae to Plants.Frontiers in plant science · 2017Article
- The influence of photoperiod and light intensity on the growth and photosynthesis of Dunaliella salina (chlorophyta) CCAP 19/30.Plant physiology and biochemistry : PPB · 2016Article
- Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes.Global change biology · 2016Review
- Label-free quantitative analysis of the casein kinase 2-responsive phosphoproteome of the marine minimal model species Ostreococcus tauri.Proteomics · 2015Article
- Predictive analytics of environmental adaptability in multi-omic network models.Scientific reports · 2015Article
- Interaction of Temperature and Photoperiod Increases Growth and Oil Content in the Marine Microalgae Dunaliella viridis.PloS one · 2015Article
- An improved genome of the model marine alga Ostreococcus tauri unfolds by assessing Illumina de novo assemblies.BMC genomics · 2014Article
- Surveillance of C-allocation in microalgal cells.Metabolites · 2014Article
- Regulatory principles and experimental approaches to the circadian control of starch turnover.Journal of the Royal Society, Interface · 2014Article
- Analysis of omics data with genome-scale models of metabolism.Molecular bioSystems · 2013Review
- What mRNA Abundances Can Tell us about Metabolism.Metabolites · 2012Article
- Mass spectrometry-based metabolomics to elucidate functions in marine organisms and ecosystems.Marine drugs · 2012Review
- Correlation of gene expression and protein production rate - a system wide study.BMC genomics · 2011Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundThe storage of photosynthetic carbohydrate products such as starch is subject to complex regulation, effected at both transcriptional and post-translational levels. The relevant genes in plants show pronounced daily regulation. Their temporal RNA expression profiles, however, do not predict the dynamics of metabolite levels, due to the divergence of enzyme activity from the RNA profiles.Unicellular phytoplankton retains the complexity of plant carbohydrate metabolism, and recent transcriptomic profiling suggests a major input of transcriptional regulation.
resultsWe used a quasi-steady-state, constraint-based modelling approach to infer the dynamics of starch content during the 12 h light/12 h dark cycle in the model alga Ostreococcus tauri. Measured RNA expression datasets from microarray analysis were integrated with a detailed stoichiometric reconstruction of starch metabolism in O. tauri in order to predict the optimal flux distribution and the dynamics of the starch content in the light/dark cycle. The predicted starch profile was validated by experimental data over the 24 h cycle. The main genetic regulatory targets within the pathway were predicted by in silico analysis.
conclusionsA single-reaction description of starch production is not able to account for the observed variability of diurnal activity profiles of starch-related enzymes. We developed a detailed reaction model of starch metabolism, which, to our knowledge, is the first attempt to describe this polysaccharide polymerization while preserving the mass balance relationships. Our model and method demonstrate the utility of a quasi-steady-state approach for inferring dynamic metabolic information in O. tauri directly from time-series gene expression data.
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