Evidence map›Paper›PMID 27553851›Full record

ArticleMicrobial cell factories2016

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

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

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 71 citations in OpenAlex.

  1. Article
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  5. Frontiers in microbiology · 2025
    Review
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  15. Article
  16. Fermentation process for producing CFAs using Yarrowia lipolytica.Journal of industrial microbiology & biotechnology · 2020
    Article
  17. Growth Behavior of SelectedFrontiers in bioengineering and biotechnology · 2020
    Article
  18. Recombinant β-Carotene Production byFrontiers in bioengineering and biotechnology · 2020
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Alexandre BackUniv. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000, Lille, France.
Tristan RossignolMicalis Institute, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-En-Josas, France.
François KrierUniv. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000, Lille, France. Francois.Krier@univ-lille1.fr.
Jean-Marc NicaudMicalis Institute, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-En-Josas, France.
Pascal DhulsterUniv. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d'Opale, EA 7394-ICV- Institut Charles Viollette, F-59000, Lille, France.
Microbiologie de l’alimentation au service de la santé · FRUniversité de Lille · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBecause 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.

resultsThe 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.

conclusionTo 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.

Indexed as

BiomassFermentationAmmonium ChlorideBioreactorsGlycerolHigh-Throughput Screening AssaysLipid MetabolismLipidsTime FactorsYarrowiaAmmonium ChlorideGlycerolLipidsHigh throughputLipid productionScreeningYarrowia lipolytica

Identifiers

PMID27553851
PMCPMC4995649
OpenAlexW2513079084

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.