↓ Skip to main content

Droplet-based microfluidic high-throughput screening of heterologous enzymes secreted by the yeast Yarrowia lipolytica

Overview of attention for article published in Microbial Cell Factories, January 2017
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
1 X user
patent
8 patents

Readers on

mendeley
304 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Droplet-based microfluidic high-throughput screening of heterologous enzymes secreted by the yeast Yarrowia lipolytica
Published in
Microbial Cell Factories, January 2017
DOI 10.1186/s12934-017-0629-5
Pubmed ID
Authors

Thomas Beneyton, Stéphane Thomas, Andrew D. Griffiths, Jean-Marc Nicaud, Antoine Drevelle, Tristan Rossignol

Abstract

Droplet-based microfluidics is becoming an increasingly attractive alternative to microtiter plate techniques for enzymatic high-throughput screening (HTS), especially for exploring large diversities with lower time and cost footprint. In this case, the assayed enzyme has to be accessible to the substrate within the water-in-oil droplet by being ideally extracellular or displayed at the cell surface. However, most of the enzymes screened to date are expressed within the cytoplasm of Escherichia coli cells, which means that a lysis step must take place inside the droplets for enzyme activity to be assayed. Here, we take advantage of the excellent secretion abilities of the yeast Yarrowia lipolytica to describe a highly efficient expression system particularly suitable for the droplet-based microfluidic HTS. Five hydrolytic genes from Aspergillus niger genome were chosen and the corresponding five Yarrowia lipolytica producing strains were constructed. Each enzyme (endo-β-1,4-xylanase B and C; 1,4-β-cellobiohydrolase A; endoglucanase A; aspartic protease) was successfully overexpressed and secreted in an active form in the crude supernatant. A droplet-based microfluidic HTS system was developed to (a) encapsulate single yeast cells; (b) grow yeast in droplets; (c) inject the relevant enzymatic substrate; (d) incubate droplets on chip; (e) detect enzymatic activity; and (f) sort droplets based on enzymatic activity. Combining this integrated microfluidic platform with gene expression in Y. lipolytica results in remarkably low variability in the enzymatic activity at the single cell level within a given monoclonal population (<5%). Xylanase, cellobiohydrolase and protease activities were successfully assayed using this system. We then used the system to screen for thermostable variants of endo-β-1,4-xylanase C in error-prone PCR libraries. Variants displaying higher thermostable xylanase activities compared to the wild-type were isolated (up to 4.7-fold improvement). Yarrowia lipolytica was used to express fungal genes encoding hydrolytic enzymes of interest. We developed a successful droplet-based microfluidic platform for the high-throughput screening (10(5) strains/h) of Y. lipolytica based on enzyme secretion and activity. This approach provides highly efficient tools for the HTS of recombinant enzymatic activities. This should be extremely useful for discovering new biocatalysts via directed evolution or protein engineering approaches and should lead to major advances in microbial cell factory development.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 304 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 <1%
Denmark 1 <1%
Unknown 302 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 63 21%
Researcher 54 18%
Student > Master 41 13%
Student > Doctoral Student 20 7%
Student > Bachelor 20 7%
Other 30 10%
Unknown 76 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 82 27%
Agricultural and Biological Sciences 45 15%
Engineering 27 9%
Chemistry 22 7%
Chemical Engineering 18 6%
Other 27 9%
Unknown 83 27%
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 19 March 2024.
All research outputs
#6,535,210
of 23,153,849 outputs
Outputs from Microbial Cell Factories
#440
of 1,620 outputs
Outputs of similar age
#124,361
of 421,015 outputs
Outputs of similar age from Microbial Cell Factories
#8
of 33 outputs
Altmetric has tracked 23,153,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,620 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 72% 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 421,015 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 69% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.