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Identification of novel metabolic interactions controlling carbon flux from xylose to ethanol in natural and recombinant yeasts

Overview of attention for article published in Biotechnology for Biofuels, September 2015
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Title
Identification of novel metabolic interactions controlling carbon flux from xylose to ethanol in natural and recombinant yeasts
Published in
Biotechnology for Biofuels, September 2015
DOI 10.1186/s13068-015-0340-x
Pubmed ID
Authors

Gert Trausinger, Christoph Gruber, Stefan Krahulec, Christoph Magnes, Bernd Nidetzky, Mario Klimacek

Abstract

Unlike xylose-converting natural yeasts, recombinant strains of Saccharomyces cerevisiae expressing the same xylose assimilation pathway produce under anaerobic conditions xylitol rather than ethanol from xylose at low specific xylose conversion rates. Despite intense research efforts over the last two decades, differences in these phenotypes cannot be explained by current metabolic and kinetic models. To improve our understanding how metabolic flux of xylose carbon to ethanol is controlled, we developed a novel kinetic model based on enzyme mechanisms and applied quantitative metabolite profiling together with enzyme activity analysis to study xylose-to-ethanol metabolisms of Candida tenuis CBS4435 (q xylose = 0.10 g/gdc/h, 25 °C; Y ethanol = 0.44 g/g; Y xylitol = 0.09 g/g) and the recombinant S. cerevisiae strain BP000 (q xylose = 0.07 g/gdc/h, 30 °C; Y ethanol = 0.24 g/g; Y xylitol = 0.43 g/g), both expressing the same xylose reductase (XR), comprehensively. Results from strain-to-strain metabolic control analysis indicated that activity levels of XR and the maximal flux capacity of the upper glycolysis (UG; both ≥ tenfold higher in CBS4435) contributed predominantly to phenotype differentiation while reactions from the oxidative pentose phosphate pathway played minor roles. Intracellular metabolite profiles supported results obtained from kinetic modeling and indicated a positive correlation between pool sizes of UG metabolites and carbon flux through the UG. For CBS4435, fast carbon flux through the UG could be associated with an allosteric control of 6-phosphofructokinase (PFK) activity by fructose 6-phosphate. The ability of CBS4435 to keep UG metabolites at high levels could be explained by low glycerol 3-phosphate phosphatase (GPP, 17-fold lower in CBS4435) and high XR activities. By applying a systems biology approach in which we combined results obtained from metabolic control analysis based on kinetic modeling with data obtained from quantitative metabolite profiling and enzyme activity analyses, we could provide new insights into metabolic and kinetic interactions contributing to the control of carbon flux from xylose to ethanol. Supported by evidences presented two new targets, PFK and GPP, could be identified that aside from XR play pivotal roles in phenotype differentiation. Design of efficient and fast microbial ethanol producers in the future can certainly benefit from results presented in this study.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Austria 2 4%
Thailand 1 2%
Brazil 1 2%
Unknown 47 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Ph. D. Student 10 20%
Student > Master 7 14%
Other 4 8%
Student > Doctoral Student 3 6%
Other 8 16%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 35%
Biochemistry, Genetics and Molecular Biology 11 22%
Chemistry 5 10%
Engineering 4 8%
Medicine and Dentistry 3 6%
Other 6 12%
Unknown 4 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 September 2015.
All research outputs
#5,467,323
of 6,417,267 outputs
Outputs from Biotechnology for Biofuels
#397
of 497 outputs
Outputs of similar age
#160,410
of 201,260 outputs
Outputs of similar age from Biotechnology for Biofuels
#11
of 16 outputs
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So far Altmetric has tracked 497 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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