↓ Skip to main content

High-throughput fermentation screening for the yeast Yarrowia lipolytica with real-time monitoring of biomass and lipid production

Overview of attention for article published in Microbial Cell Factories, August 2016
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
153 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
High-throughput fermentation screening for the yeast Yarrowia lipolytica with real-time monitoring of biomass and lipid production
Published in
Microbial Cell Factories, August 2016
DOI 10.1186/s12934-016-0546-z
Pubmed ID
Authors

Alexandre Back, Tristan Rossignol, François Krier, Jean-Marc Nicaud, Pascal Dhulster

Abstract

Because the model yeast Yarrowia lipolytica can synthesize and store lipids in quantities up to 20 % of its dry weight, it is a promising microorganism for oil production at an industrial scale. Typically, optimization of the lipid production process is performed in the laboratory and later scaled up for industrial production. However, the scale-up process can be complicated by genetic modifications that are optimized for one set of growing conditions can confer a less-than-optimal phenotype in a different environment. To address this issue, small cultivation systems have been developed that mimic the conditions in benchtop bioreactors. In this work, we used one such microbioreactor system, the BioLector, to develop high-throughput fermentation procedures that optimize growth and lipid accumulation in Y. lipolytica. Using this system, we were able to monitor lipid and biomass production in real time throughout the culture duration. The BioLector can monitor the growth of Y. lipolytica in real time by evaluating scattered light; this produced accurate measurements until cultures reached an equivalent of OD600nm = 115 and a cell dry weight of 100 g L(-1). In addition, a lipid-specific fluorescent probe was applied which reliably monitored lipid production up to a concentration of 12 g L(-1). Through screening various growing conditions, we determined that a carbon/nitrogen ratio of 35 was the most efficient for lipid production. Further screening showed that ammonium chloride and glycerol were the most valuable nitrogen and carbon sources, respectively, for growth and lipid production. Moreover, a carbon concentration above 1 M appeared to impair growth and lipid accumulation. Finally, we used these optimized conditions to screen engineered strains of Y. lipolytica with high lipid-accumulation capability. The growth and lipid content of the strains cultivated in the BioLector were compared to those grown in benchtop bioreactors. To our knowledge, this is the first time that the BioLector has been used to track lipid production in real time and to monitor the growth of Y. lipolytica. The present study also showed the efficacy of the BioLector in screening growing conditions and engineered strains prior to scale-up. The method described here could be applied to other oleaginous microorganisms.

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 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 <1%
Germany 1 <1%
Unknown 151 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 21%
Researcher 26 17%
Student > Master 22 14%
Student > Bachelor 16 10%
Student > Doctoral Student 9 6%
Other 11 7%
Unknown 37 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 43 28%
Agricultural and Biological Sciences 24 16%
Chemical Engineering 17 11%
Engineering 15 10%
Chemistry 3 2%
Other 9 6%
Unknown 42 27%
Attention Score in Context

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 25 August 2016.
All research outputs
#20,337,788
of 22,883,326 outputs
Outputs from Microbial Cell Factories
#1,366
of 1,603 outputs
Outputs of similar age
#299,353
of 342,845 outputs
Outputs of similar age from Microbial Cell Factories
#29
of 40 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,603 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 1st percentile – i.e., 1% 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 342,845 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.