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Engineering of protein secretion in yeast: strategies and impact on protein production

Overview of attention for article published in Applied Microbiology and Biotechnology, February 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

patent
9 patents
facebook
1 Facebook page

Citations

dimensions_citation
261 Dimensions

Readers on

mendeley
614 Mendeley
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1 CiteULike
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Title
Engineering of protein secretion in yeast: strategies and impact on protein production
Published in
Applied Microbiology and Biotechnology, February 2010
DOI 10.1007/s00253-010-2447-0
Pubmed ID
Authors

Alimjan Idiris, Hideki Tohda, Hiromichi Kumagai, Kaoru Takegawa

Abstract

Yeasts combine the ease of genetic manipulation and fermentation of a microorganism with the capability to secrete and modify foreign proteins according to a general eukaryotic scheme. Their rapid growth, microbiological safety, and high-density fermentation in simplified medium have a high impact particularly in the large-scale industrial production of foreign proteins, where secretory expression is important for simplifying the downstream protein purification process. However, secretory expression of heterologous proteins in yeast is often subject to several bottlenecks that limit yield. Thus, many studies on yeast secretion systems have focused on the engineering of the fermentation process, vector systems, and host strains. Recently, strain engineering by genetic modification has been the most useful and effective method for overcoming the drawbacks in yeast secretion pathways. Such an approach is now being promoted strongly by current post-genomic technology and system biology tools. However, engineering of the yeast secretion system is complicated by the involvement of many cross-reacting factors. Tight interdependence of each of these factors makes genetic modification difficult. This indicates the necessity of developing a novel systematic modification strategy for genetic engineering of the yeast secretion system. This mini-review focuses on recent strategies and their advantages for systematic engineering of yeast strains for effective protein secretion.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 614 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 6 <1%
Austria 4 <1%
Brazil 4 <1%
Germany 4 <1%
United States 4 <1%
United Kingdom 4 <1%
France 2 <1%
Mexico 2 <1%
Czechia 1 <1%
Other 6 <1%
Unknown 577 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 153 25%
Student > Master 94 15%
Researcher 93 15%
Student > Bachelor 70 11%
Student > Doctoral Student 29 5%
Other 77 13%
Unknown 98 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 248 40%
Biochemistry, Genetics and Molecular Biology 149 24%
Engineering 32 5%
Chemistry 22 4%
Chemical Engineering 19 3%
Other 35 6%
Unknown 109 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 04 October 2022.
All research outputs
#7,764,167
of 24,119,703 outputs
Outputs from Applied Microbiology and Biotechnology
#2,616
of 8,034 outputs
Outputs of similar age
#49,752
of 171,793 outputs
Outputs of similar age from Applied Microbiology and Biotechnology
#24
of 50 outputs
Altmetric has tracked 24,119,703 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 8,034 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 65% 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 171,793 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 70% 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 52% of its contemporaries.