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Analysis of Sensitive CO2 Pathways and Genes Related to Carbon Uptake and Accumulation in Chlamydomonas reinhardtii through Genomic Scale Modeling and Experimental Validation

Overview of attention for article published in Frontiers in Plant Science, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 blog
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1 Facebook page

Citations

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20 Dimensions

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81 Mendeley
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Title
Analysis of Sensitive CO2 Pathways and Genes Related to Carbon Uptake and Accumulation in Chlamydomonas reinhardtii through Genomic Scale Modeling and Experimental Validation
Published in
Frontiers in Plant Science, February 2016
DOI 10.3389/fpls.2016.00043
Pubmed ID
Authors

Flavia V. Winck, David O. Páez Melo, Diego M. Riaño-Pachón, Marina C. M. Martins, Camila Caldana, Andrés F. González Barrios

Abstract

The development of microalgae sustainable applications needs better understanding of microalgae biology. Moreover, how cells coordinate their metabolism toward biomass accumulation is not fully understood. In this present study, flux balance analysis (FBA) was performed to identify sensitive metabolic pathways of Chlamydomonas reinhardtii under varied CO2 inputs. The metabolic network model of Chlamydomonas was updated based on the genome annotation data and sensitivity analysis revealed CO2 sensitive reactions. Biological experiments were performed with cells cultivated at 0.04% (air), 2.5, 5, 8, and 10% CO2 concentration under controlled conditions and cell growth profiles and biomass content were measured. Pigments, lipids, proteins, and starch were further quantified for the reference low (0.04%) and high (10%) CO2 conditions. The expression level of candidate genes of sensitive reactions was measured and validated by quantitative real time PCR. The sensitive analysis revealed mitochondrial compartment as the major affected by changes on the CO2 concentrations and glycolysis/gluconeogenesis, glyoxylate, and dicarboxylate metabolism among the affected metabolic pathways. Genes coding for glycerate kinase (GLYK), glycine cleavage system, H-protein (GCSH), NAD-dependent malate dehydrogenase (MDH3), low-CO2 inducible protein A (LCIA), carbonic anhydrase 5 (CAH5), E1 component, alpha subunit (PDC3), dual function alcohol dehydrogenase/acetaldehyde dehydrogenase (ADH1), and phosphoglucomutase (GPM2), were defined, among other genes, as sensitive nodes in the metabolic network simulations. These genes were experimentally responsive to the changes in the carbon fluxes in the system. We performed metabolomics analysis using mass spectrometry validating the modulation of carbon dioxide responsive pathways and metabolites. The changes on CO2 levels mostly affected the metabolism of amino acids found in the photorespiration pathway. Our updated metabolic network was compared to previous model and it showed more consistent results once considering the experimental data. Possible roles of the sensitive pathways in the biomass metabolism are discussed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Brazil 1 1%
Unknown 79 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 20%
Researcher 16 20%
Student > Bachelor 9 11%
Student > Doctoral Student 7 9%
Student > Master 6 7%
Other 10 12%
Unknown 17 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 31%
Biochemistry, Genetics and Molecular Biology 18 22%
Engineering 7 9%
Chemical Engineering 4 5%
Neuroscience 2 2%
Other 7 9%
Unknown 18 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 December 2016.
All research outputs
#3,573,190
of 22,837,982 outputs
Outputs from Frontiers in Plant Science
#1,726
of 20,160 outputs
Outputs of similar age
#64,916
of 400,364 outputs
Outputs of similar age from Frontiers in Plant Science
#30
of 486 outputs
Altmetric has tracked 22,837,982 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,160 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 400,364 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 486 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.