Rapid detection of intracellular lipid content in oleaginous yeast
Rhodotorula glutinis
Motivation/Introduction
Acknowledgements/References
Conclusions and Outlook
a Technische Universität Berlin, Department of Biotechnology, Chair of Bioprocess Engineering,
Ackerstrasse 76 ACK24, D-13355 Berlin, http://www.bioprocess.tu-berlin.de
b Research and Teaching Institute for Brewing in Berlin, Department Bioprocess Engineering and Applied
Microbiology, Seestrasse 13, D-13353 Berlin, http://www.vlb-berlin.org/beam
Lorenz, E.a, Runge, D.a, Ngo, H. T. A.a, Marbà-Ardébol, A. M.a, Schmacht, M.b, Junne, S.a, Neubauer, P. a, Senz, M.b
The objective of the cooperative project FENA is the partial substitution of fish meal and fish oil by algae and oleaginous yeast for a sustainable and high-value fish
nutrition. Oleaginous yeasts are characterized by lipid contents of more than 20 % (Ratledge and Cohen 2005). They are able to accumulate up to 70 % of lipid of their own
mass (Ageitos et al., 2011). Typical representative yeast genera are Candida, Cryptococcus, Lipomyces, Yarrowia, Rhodosporidium and of course Rhodotorula.
Rhodotorula glutinis is an often used organism with a wide range of industrial usage reaching from biodiesel to carotenoids or as feed for breeding animals as well as
potential producer of industrial enzymes for food industry (Kot et al., 2016). For accumulation of high lipid contents, the limitation of minimum one or more essential
nutrients for cell proliferation, e.g. nitrogen, phosphor, iron, zinc or magnesium, is required. However, for biotechnology applications nitrogen limitation is preferably used to
induce lipid accumulation (Beopoulos et al., 2009; Granger et al., 1993). Therefore, cultivations of oleaginous yeasts are usually carried out in a medium with a high C to N
ratio. As long as nitrogen is present, the organism proliferates and produces (mainly lipid-free) biomass. After exhaustion of nitrogen, cell proliferation slows down and the
remaining carbon source is channeled into lipid formation.
For the development of a fermentation process, there are a lot of optimization parameters, e.g. medium components, C/N-ratio, pH, DO or temperature. Therefore, process
development takes a lot of time and experiments resulting in a large amount of samples. The upcoming samples should be analyzed as fast as possible. Traditional
methods like the gravimetric analysis described in detail by Bligh and Dyer, 1959 or the extraction of lipids by organic solvents followed by GC-FID analysis takes several
days. We developed three different methods for a rapid detection of intracellular lipid in the oleaginous yeast R. glutinis. Thereby, flow cytometry and fluorescence
spectroscopy combined with the staining dye Nile Red were applied for fast lipid detection.
0
500
1000
1500
2000
2500
3000
480 500 520 540 560 580 600 620 640 660
465
470
475
480485
490495
500505
RF
U [-]
Emission [nm]
Anre
gung [n
m]
Concept and Results
Staining dye Nile Red
Figure 1. Kimura et al., 2004
characterized various oleaginous
yeast and fungi strains regarding
intracellular lipid content by means
of the fluorescence dye Nile Red.
This established staining method
was improved and simplified for a
rapid estimation of lipid content in
yeast, especially for R. glutinis.
Based on a wavelength screening,
the excitation and emission were
adjusted to 480 nm and 580 nm,
respectively.
96-well-plate (Nile Red)
Figure 3. Nile Red can also be used in 96-well-
plates (Greiner Inc., Fluotrac 200). Thereby,
OD600 should be adjusted in a range of 0.3 - 0.6.
200 µl cell suspension were stained with 4 µl of
100 µg∙ml-1 of Nile Red stock solutio, mixed by
pipetting and measured immediately in the
plate. 100 µl stained cell suspension was
discarded before measurement was executed.
Obtained RFU-values were divided by
previously determined OD600 (range of 0.3 -
0.6). Measurements were conducted at
480ex/580em (nm) with the Spectramax M2e
from Molecular Devices. Correlation with GC-
FID analysis resulted in an adjusted R-square of
0.889 and can be considered as valid method.
Flow cytometry (side scatter)
Figure 4. Measurements via flow cytometry
showed that side scatter (granularity) can be
used for adequate detection of intracellular
lipids. An adjusted R-square of 0.875 indicated
a strong correlation between granularity and
lipid content. In figure 2 (right) lipid drops
inside yeast cells can be direct visualized
without previous staining.
• Rapid lipid measurement is possible via photometric or flow cytometric methods
• Online lipid detection is even possible without staining via granularity (side scatter)
• Methods were proven by real HCD production process of R. glutinis with 106 g∙L-1
biomass and 65% intracellular lipid content.
Flow cytometry (Nile Red)
Figure 5. 1 ml washed cells with a concentration of
2-6∙106 cells∙ml-1 were stained with 20 µl of 100 µg∙ml-1 of Nile Red stock
solution, mixed for 5 s and measured immediately by flow cytometry.
Fluorescence signal was captured by channel FL2 (488 nm excitation and
bandpass filter 590/50). For statistically relevant evaluation, fluorescence values
of ≥1∙105 cells were recorded. This method showed among others the highest
correlation to GC-FID exhibiting an adjusted R-square of 0.959. Measurements
were executed by CyFlow® Cube 8 (Sysmex Deutschland GmbH). Exemplarily,
the progress of lipid content (histogram) measured by flow cytometry is plotted
(right).
lipid content
time
8h
10 µm
10 µm
10 µm
10 µm
10 µm
24h
32h
72h
80h
Figure 2. The final production process ensured high biomass concentrations of more 100 g∙L-1 and
60 % lipid content in a short period of time with R. glutinis. Microscopy pictures (right) visualized the
lipid accumulation during the process. Pictures were captured by using an Axio Imager M2
microscope equipped with an Axio Cam MR3 camera and a N-Achroplan 100x/1.25 oil m27 objective
(total magnification 1000x) applying the filter set 43 HE (Carl Zeiss Microscopy GmbH).
Propagation Lipid accumulation
The course of process development is often dependent on the speed of providing the analytical data. Therefore, we investigated different methods to speed up the process
development for maximizing lipid production with R. glutinis. In comparison to traditional protocols, the established methods based on flow cytometry and fluorescence
spectroscopy could significantly enhance the time of analysis and thus the time of process development from days to minutes. These detection procedures are reliable,
valid and easy to handle, indicated by high correlation quotients of up to 0.959. Further, the 96-well-plate spectroscopy assay can also be applied for extended strain
screening. As an additional rapid detection method for lipid accumulation, granularity can be measured by side scatter via flow cytometry. Therefore, it is conceivable that
an on-line integration of flow cytometry in a production facility for monitoring the lipid formation immediately without staining is of value. However, it has to be considered if
the developed methods are suitable for lipid detection in other strains as well.
Technische Universität Berlin
Single Cell Oils: microbial and algal oils / editors Z. Cohen and C. Radledge 2nd Edition, Publisher: AOCS Press Urbana, Illinois (2005)
Ageitos J M, Vallejo J A, Veiga-Crespo P, Villa T G: Oily yeasts as oleaginous cell factories. Applied Microbiology and Biotechnology 90, 1219 (2011)
Kot A M, Błazejak S, Kurcz A, Gientka I, Kieliszek M: Rhodotorula glutinis - potential source of lipids, carotenoids, and enzymes for use in industries. Applied Microbiology and Biotechnology (2016)
Beopoulos A, Chardot T, Nicaud J M: Yarrowia lipolytica: A model and a tool to understand the mechanisms implicated in lipid accumulation. Biochimie 91, 692 (2009)
Granger L-M, Perlot P, Goma G, Pareilleux A: Efficiency of fatty acid synthesis by oleaginous yeasts: Prediction of yield and fatty acid content from consumed C/N ration by a simple method. Biotechnology and Bioengineering 42, (1993)
Kimura K, Yamaoka M, Kamisaka Y: Rapid estimation of lipids in oleaginous fungi and yeasts using Nile red fluorescence. Journal of Microbiological Methods 56, (2004)