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Codon optimization of Saccharomyces cerevisiae mating factor alpha prepro-leader to improve recombinant protein production in Pichia pastoris

Overview of attention for article published in Biotechnology Techniques, September 2016
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53 Mendeley
Title
Codon optimization of Saccharomyces cerevisiae mating factor alpha prepro-leader to improve recombinant protein production in Pichia pastoris
Published in
Biotechnology Techniques, September 2016
DOI 10.1007/s10529-016-2203-3
Pubmed ID
Authors

Jungoh Ahn, Min-Jung Jang, Kok Siong Ang, Hongweon Lee, Eui-Sung Choi, Dong-Yup Lee

Abstract

To evaluate different codon optimization parameters on the Saccharomyces cerevisiae-derived mating factor α prepro-leader sequence (MFLS) to improve Candida antarctica lipase B (CAL-B) secretory production in Pichia pastoris. Codon optimization based on the individual codon usage (ICU) and codon context (CC) design parameters enhanced secretory production of CAL-B to 7 U/ml and 12 U/ml, respectively. Only 3 U/ml was obtained with the wild type sequence while the sequence optimized using both ICU and CC objectives showed intermediate performance of 10 U/ml. These results clearly show that CC is the most relevant parameter for the codon optimization of MFLS in P. pastoris, and there is no synergistic effect achieved by considering both ICU and CC together. The CC optimized MFLS increased secretory protein production of CAL-B in P. pastoris by fourfold.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 2%
Austria 1 2%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Researcher 11 21%
Student > Master 10 19%
Student > Bachelor 7 13%
Student > Postgraduate 2 4%
Other 2 4%
Unknown 10 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 38%
Agricultural and Biological Sciences 14 26%
Immunology and Microbiology 3 6%
Chemical Engineering 2 4%
Engineering 2 4%
Other 1 2%
Unknown 11 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 September 2016.
All research outputs
#16,048,009
of 25,374,647 outputs
Outputs from Biotechnology Techniques
#2,162
of 2,762 outputs
Outputs of similar age
#201,974
of 340,181 outputs
Outputs of similar age from Biotechnology Techniques
#11
of 24 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,762 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 340,181 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 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 50% of its contemporaries.