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Validation of an FBA model for Pichia pastoris in chemostat cultures

Overview of attention for article published in BMC Systems Biology, December 2014
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Title
Validation of an FBA model for Pichia pastoris in chemostat cultures
Published in
BMC Systems Biology, December 2014
DOI 10.1186/s12918-014-0142-y
Pubmed ID
Authors

Yeimy Morales, Marta Tortajada, Jesús Picó, Josep Vehí, Francisco Llaneras

Abstract

BackgroundConstraint-based metabolic models and flux balance analysis (FBA) have been extensively used in the last years to investigate the behavior of cells and also as basis for different industrial applications. In this context, this work provides a validation of a small-sized FBA model of the yeast Pichia pastoris. Our main objective is testing how accurate is the hypothesis of maximum growth to predict the behavior of P. pastoris in a range of experimental environments.ResultsA constraint-based model of P. pastoris was previously validated using metabolic flux analysis (MFA). In this paper we have verified the model ability to predict the cells behavior in different conditions without introducing measurements, experimental parameters, or any additional constraint, just by assuming that cells will make the best use of the available resources to maximize its growth. In particular, we have tested FBA model ability to: (a) predict growth yields over single substrates (glucose, glycerol, and methanol); (b) predict growth rate, substrate uptakes, respiration rates, and by-product formation in scenarios where different substrates are available (glucose, glycerol, methanol, or mixes of methanol and glycerol); (c) predict the different behaviors of P. pastoris cultures in aerobic and hypoxic conditions for each single substrate. In every case, experimental data from literature are used as validation.ConclusionsWe conclude that our predictions based on growth maximisation are reasonably accurate, but still far from perfect. The deviations are significant in scenarios where P. pastoris grows on methanol, suggesting that the hypothesis of maximum growth could be not dominating in these situations. However, predictions are much better when glycerol or glucose are used as substrates. In these scenarios, even if our FBA model is small and imposes a strong assumption regarding how cells will regulate their metabolic fluxes, it provides reasonably good predictions in terms of growth, substrate preference, product formation, and respiration rates.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
India 1 1%
Netherlands 1 1%
Sweden 1 1%
Unknown 72 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 30%
Researcher 18 23%
Student > Master 9 12%
Student > Doctoral Student 5 6%
Student > Bachelor 4 5%
Other 12 16%
Unknown 6 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 29%
Biochemistry, Genetics and Molecular Biology 19 25%
Engineering 11 14%
Chemical Engineering 6 8%
Computer Science 3 4%
Other 3 4%
Unknown 13 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 14 July 2016.
All research outputs
#13,344,161
of 22,775,504 outputs
Outputs from BMC Systems Biology
#472
of 1,142 outputs
Outputs of similar age
#171,555
of 353,020 outputs
Outputs of similar age from BMC Systems Biology
#17
of 50 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 58% 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 353,020 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.